semantic cleanup

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2026-05-08 10:07:05 +03:00
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---
description: USE SEMANTIC
---
Прочитай .ai/standards/semantics.md. ОБЯЗАТЕЛЬНО используй его при разработке

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---
description: Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Goal
Identify inconsistencies, duplications, ambiguities, underspecified items, and decision-memory drift across the core artifacts (`spec.md`, `plan.md`, `tasks.md`, and ADR sources) before implementation. This command MUST run only after `/speckit.tasks` has successfully produced a complete `tasks.md`.
## Operating Constraints
**STRICTLY READ-ONLY**: Do **not** modify any files. Output a structured analysis report. Offer an optional remediation plan (user must explicitly approve before any follow-up editing commands would be invoked manually).
**Constitution Authority**: The project constitution (`.ai/standards/constitution.md`) is **non-negotiable** within this analysis scope. Constitution conflicts are automatically CRITICAL and require adjustment of the spec, plan, or tasks—not dilution, reinterpretation, or silent ignoring of the principle. If a principle itself needs to change, that must occur in a separate, explicit constitution update outside `/speckit.analyze`.
## Execution Steps
### 1. Initialize Analysis Context
Run `.specify/scripts/bash/check-prerequisites.sh --json --require-tasks --include-tasks` once from repo root and parse JSON for FEATURE_DIR and AVAILABLE_DOCS. Derive absolute paths:
- SPEC = FEATURE_DIR/spec.md
- PLAN = FEATURE_DIR/plan.md
- TASKS = FEATURE_DIR/tasks.md
- ADR = `docs/architecture.md` and/or feature-local decision files when present
Abort with an error message if any required file is missing (instruct the user to run missing prerequisite command).
For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
### 2. Load Artifacts (Progressive Disclosure)
Load only the minimal necessary context from each artifact:
**From `spec.md`:**
- Overview/Context
- Functional Requirements
- Non-Functional Requirements
- User Stories
- Edge Cases (if present)
**From `plan.md`:**
- Architecture/stack choices
- Data Model references
- Phases
- Technical constraints
- ADR references or emitted decisions
**From `tasks.md`:**
- Task IDs
- Descriptions
- Phase grouping
- Parallel markers [P]
- Referenced file paths
- Guardrail summaries derived from `@RATIONALE` / `@REJECTED`
**From ADR sources:**
- `[DEF:id:ADR]` nodes
- `@RATIONALE`
- `@REJECTED`
- `@RELATION`
**From constitution:**
- Load `.ai/standards/constitution.md` for principle validation
- Load `.ai/standards/semantics.md` for technical standard validation
### 3. Build Semantic Models
Create internal representations (do not include raw artifacts in output):
- **Requirements inventory**: Each functional + non-functional requirement with a stable key (derive slug based on imperative phrase; e.g., "User can upload file" → `user-can-upload-file`)
- **User story/action inventory**: Discrete user actions with acceptance criteria
- **Task coverage mapping**: Map each task to one or more requirements or stories (inference by keyword / explicit reference patterns like IDs or key phrases)
- **Constitution rule set**: Extract principle names and MUST/SHOULD normative statements
- **Decision-memory inventory**: ADR ids, accepted paths, rejected paths, and the tasks/contracts expected to inherit them
### 4. Detection Passes (Token-Efficient Analysis)
Focus on high-signal findings. Limit to 50 findings total; aggregate remainder in overflow summary.
#### A. Duplication Detection
- Identify near-duplicate requirements
- Mark lower-quality phrasing for consolidation
#### B. Ambiguity Detection
- Flag vague adjectives (fast, scalable, secure, intuitive, robust) lacking measurable criteria
- Flag unresolved placeholders (TODO, TKTK, ???, `<placeholder>`, etc.)
#### C. Underspecification
- Requirements with verbs but missing object or measurable outcome
- User stories missing acceptance criteria alignment
- Tasks referencing files or components not defined in spec/plan
#### D. Constitution Alignment
- Any requirement or plan element conflicting with a MUST principle
- Missing mandated sections or quality gates from constitution
#### E. Coverage Gaps
- Requirements with zero associated tasks
- Tasks with no mapped requirement/story
- Non-functional requirements not reflected in tasks (e.g., performance, security)
#### F. Inconsistency
- Terminology drift (same concept named differently across files)
- Data entities referenced in plan but absent in spec (or vice versa)
- Task ordering contradictions (e.g., integration tasks before foundational setup tasks without dependency note)
- Conflicting requirements (e.g., one requires Next.js while other specifies Vue)
#### G. Decision-Memory Drift
- ADR exists in planning but has no downstream task guardrail
- Task carries a guardrail with no upstream ADR or plan rationale
- Task text accidentally schedules an ADR-rejected path
- Missing preventive `@RATIONALE` / `@REJECTED` summaries for known traps
- Rejected-path notes that contradict later plan or task language without explicit decision revision
### 5. Severity Assignment
Use this heuristic to prioritize findings:
- **CRITICAL**: Violates constitution MUST, missing core spec artifact, missing blocking ADR, rejected path scheduled as work, or requirement with zero coverage that blocks baseline functionality
- **HIGH**: Duplicate or conflicting requirement, ambiguous security/performance attribute, untestable acceptance criterion, ADR guardrail drift
- **MEDIUM**: Terminology drift, missing non-functional task coverage, underspecified edge case, incomplete decision-memory propagation
- **LOW**: Style/wording improvements, minor redundancy not affecting execution order
### 6. Produce Compact Analysis Report
Output a Markdown report (no file writes) with the following structure:
## Specification Analysis Report
| ID | Category | Severity | Location(s) | Summary | Recommendation |
|----|----------|----------|-------------|---------|----------------|
| A1 | Duplication | HIGH | spec.md:L120-134 | Two similar requirements ... | Merge phrasing; keep clearer version |
(Add one row per finding; generate stable IDs prefixed by category initial.)
**Coverage Summary Table:**
| Requirement Key | Has Task? | Task IDs | Notes |
|-----------------|-----------|----------|-------|
**Decision Memory Summary Table:**
| ADR / Guardrail | Present in Plan | Propagated to Tasks | Rejected Path Protected | Notes |
|-----------------|-----------------|---------------------|-------------------------|-------|
**Constitution Alignment Issues:** (if any)
**Unmapped Tasks:** (if any)
**Metrics:**
- Total Requirements
- Total Tasks
- Coverage % (requirements with >=1 task)
- Ambiguity Count
- Duplication Count
- Critical Issues Count
- ADR Count
- Guardrail Drift Count
### 7. Provide Next Actions
At end of report, output a concise Next Actions block:
- If CRITICAL issues exist: Recommend resolving before `/speckit.implement`
- If only LOW/MEDIUM: User may proceed, but provide improvement suggestions
- Provide explicit command suggestions: e.g., "Run /speckit.specify with refinement", "Run /speckit.plan to adjust architecture", "Manually edit tasks.md to add coverage for 'performance-metrics'"
### 8. Offer Remediation
Ask the user: "Would you like me to suggest concrete remediation edits for the top N issues?" (Do NOT apply them automatically.)
## Operating Principles
### Context Efficiency
- **Minimal high-signal tokens**: Focus on actionable findings, not exhaustive documentation
- **Progressive disclosure**: Load artifacts incrementally; don't dump all content into analysis
- **Token-efficient output**: Limit findings table to 50 rows; summarize overflow
- **Deterministic results**: Rerunning without changes should produce consistent IDs and counts
### Analysis Guidelines
- **NEVER modify files** (this is read-only analysis)
- **NEVER hallucinate missing sections** (if absent, report them accurately)
- **Prioritize constitution violations** (these are always CRITICAL)
- **Use examples over exhaustive rules** (cite specific instances, not generic patterns)
- **Report zero issues gracefully** (emit success report with coverage statistics)
- **Treat missing ADR propagation as a real defect, not a documentation nit**
## Context
$ARGUMENTS

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---
description: Generate a custom checklist for the current feature based on user requirements.
---
## Checklist Purpose: "Unit Tests for English"
**CRITICAL CONCEPT**: Checklists are **UNIT TESTS FOR REQUIREMENTS WRITING** - they validate the quality, clarity, completeness, and decision-memory readiness of requirements in a given domain.
**NOT for verification/testing**:
- ❌ NOT "Verify the button clicks correctly"
- ❌ NOT "Test error handling works"
- ❌ NOT "Confirm the API returns 200"
- ❌ NOT checking if code/implementation matches the spec
**FOR requirements quality validation**:
- ✅ "Are visual hierarchy requirements defined for all card types?" (completeness)
- ✅ "Is 'prominent display' quantified with specific sizing/positioning?" (clarity)
- ✅ "Are hover state requirements consistent across all interactive elements?" (consistency)
- ✅ "Are accessibility requirements defined for keyboard navigation?" (coverage)
- ✅ "Does the spec define what happens when logo image fails to load?" (edge cases)
- ✅ "Do repo-shaping choices have explicit rationale and rejected alternatives before task decomposition?" (decision memory)
**Metaphor**: If your spec is code written in English, the checklist is its unit test suite. You're testing whether the requirements are well-written, complete, unambiguous, and ready for implementation - NOT whether the implementation works.
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Execution Steps
1. **Setup**: Run `.specify/scripts/bash/check-prerequisites.sh --json` from repo root and parse JSON for FEATURE_DIR and AVAILABLE_DOCS list.
- All file paths must be absolute.
- For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Clarify intent (dynamic)**: Derive up to THREE initial contextual clarifying questions (no pre-baked catalog). They MUST:
- Be generated from the user's phrasing + extracted signals from spec/plan/tasks
- Only ask about information that materially changes checklist content
- Be skipped individually if already unambiguous in `$ARGUMENTS`
- Prefer precision over breadth
Generation algorithm:
1. Extract signals: feature domain keywords (e.g., auth, latency, UX, API), risk indicators ("critical", "must", "compliance"), stakeholder hints ("QA", "review", "security team"), and explicit deliverables ("a11y", "rollback", "contracts").
2. Cluster signals into candidate focus areas (max 4) ranked by relevance.
3. Identify probable audience & timing (author, reviewer, QA, release) if not explicit.
4. Detect missing dimensions: scope breadth, depth/rigor, risk emphasis, exclusion boundaries, measurable acceptance criteria, decision-memory needs.
5. Formulate questions chosen from these archetypes:
- Scope refinement (e.g., "Should this include integration touchpoints with X and Y or stay limited to local module correctness?")
- Risk prioritization (e.g., "Which of these potential risk areas should receive mandatory gating checks?")
- Depth calibration (e.g., "Is this a lightweight pre-commit sanity list or a formal release gate?")
- Audience framing (e.g., "Will this be used by the author only or peers during PR review?")
- Boundary exclusion (e.g., "Should we explicitly exclude performance tuning items this round?")
- Scenario class gap (e.g., "No recovery flows detected—are rollback / partial failure paths in scope?")
- Decision-memory gap (e.g., "Do we need explicit ADR and rejected-path checks for this feature?")
Question formatting rules:
- If presenting options, generate a compact table with columns: Option | Candidate | Why It Matters
- Limit to AE options maximum; omit table if a free-form answer is clearer
- Never ask the user to restate what they already said
- Avoid speculative categories (no hallucination). If uncertain, ask explicitly: "Confirm whether X belongs in scope."
Defaults when interaction impossible:
- Depth: Standard
- Audience: Reviewer (PR) if code-related; Author otherwise
- Focus: Top 2 relevance clusters
Output the questions (label Q1/Q2/Q3). After answers: if ≥2 scenario classes (Alternate / Exception / Recovery / Non-Functional domain) remain unclear, you MAY ask up to TWO more targeted followups (Q4/Q5) with a one-line justification each (e.g., "Unresolved recovery path risk"). Do not exceed five total questions. Skip escalation if user explicitly declines more.
3. **Understand user request**: Combine `$ARGUMENTS` + clarifying answers:
- Derive checklist theme (e.g., security, review, deploy, ux)
- Consolidate explicit must-have items mentioned by user
- Map focus selections to category scaffolding
- Infer any missing context from spec/plan/tasks (do NOT hallucinate)
4. **Load feature context**: Read from FEATURE_DIR:
- `spec.md`: Feature requirements and scope
- `plan.md` (if exists): Technical details, dependencies, ADR references
- `tasks.md` (if exists): Implementation tasks and inherited guardrails
- ADR artifacts (if present): `[DEF:id:ADR]`, `@RATIONALE`, `@REJECTED`
**Context Loading Strategy**:
- Load only necessary portions relevant to active focus areas (avoid full-file dumping)
- Prefer summarizing long sections into concise scenario/requirement bullets
- Use progressive disclosure: add follow-on retrieval only if gaps detected
- If source docs are large, generate interim summary items instead of embedding raw text
5. **Generate checklist** - Create "Unit Tests for Requirements":
- Create `FEATURE_DIR/checklists/` directory if it doesn't exist
- Generate unique checklist filename:
- Use short, descriptive name based on domain (e.g., `ux.md`, `api.md`, `security.md`)
- Format: `[domain].md`
- If file exists, append to existing file
- Number items sequentially starting from CHK001
- Each `/speckit.checklist` run creates a NEW file (never overwrites existing checklists)
**CORE PRINCIPLE - Test the Requirements, Not the Implementation**:
Every checklist item MUST evaluate the REQUIREMENTS THEMSELVES for:
- **Completeness**: Are all necessary requirements present?
- **Clarity**: Are requirements unambiguous and specific?
- **Consistency**: Do requirements align with each other?
- **Measurability**: Can requirements be objectively verified?
- **Coverage**: Are all scenarios/edge cases addressed?
- **Decision Memory**: Are durable choices and rejected alternatives explicit before implementation starts?
**Category Structure** - Group items by requirement quality dimensions:
- **Requirement Completeness** (Are all necessary requirements documented?)
- **Requirement Clarity** (Are requirements specific and unambiguous?)
- **Requirement Consistency** (Do requirements align without conflicts?)
- **Acceptance Criteria Quality** (Are success criteria measurable?)
- **Scenario Coverage** (Are all flows/cases addressed?)
- **Edge Case Coverage** (Are boundary conditions defined?)
- **Non-Functional Requirements** (Performance, Security, Accessibility, etc. - are they specified?)
- **Dependencies & Assumptions** (Are they documented and validated?)
- **Decision Memory & ADRs** (Are architectural choices, rationale, and rejected paths explicit?)
- **Ambiguities & Conflicts** (What needs clarification?)
**HOW TO WRITE CHECKLIST ITEMS - "Unit Tests for English"**:
**WRONG** (Testing implementation):
- "Verify landing page displays 3 episode cards"
- "Test hover states work on desktop"
- "Confirm logo click navigates home"
**CORRECT** (Testing requirements quality):
- "Are the exact number and layout of featured episodes specified?" [Completeness]
- "Is 'prominent display' quantified with specific sizing/positioning?" [Clarity]
- "Are hover state requirements consistent across all interactive elements?" [Consistency]
- "Are keyboard navigation requirements defined for all interactive UI?" [Coverage]
- "Is the fallback behavior specified when logo image fails to load?" [Edge Cases]
- "Are blocking architecture decisions recorded with explicit rationale and rejected alternatives before task generation?" [Decision Memory]
- "Does the plan make clear which implementation shortcuts are forbidden for this feature?" [Decision Memory, Gap]
**ITEM STRUCTURE**:
Each item should follow this pattern:
- Question format asking about requirement quality
- Focus on what's WRITTEN (or not written) in the spec/plan
- Include quality dimension in brackets [Completeness/Clarity/Consistency/etc.]
- Reference spec section `[Spec §X.Y]` when checking existing requirements
- Use `[Gap]` marker when checking for missing requirements
**EXAMPLES BY QUALITY DIMENSION**:
Completeness:
- "Are error handling requirements defined for all API failure modes? [Gap]"
- "Are accessibility requirements specified for all interactive elements? [Completeness]"
- "Are mobile breakpoint requirements defined for responsive layouts? [Gap]"
Clarity:
- "Is 'fast loading' quantified with specific timing thresholds? [Clarity, Spec §NFR-2]"
- "Are 'related episodes' selection criteria explicitly defined? [Clarity, Spec §FR-5]"
- "Is 'prominent' defined with measurable visual properties? [Ambiguity, Spec §FR-4]"
Consistency:
- "Do navigation requirements align across all pages? [Consistency, Spec §FR-10]"
- "Are card component requirements consistent between landing and detail pages? [Consistency]"
Coverage:
- "Are requirements defined for zero-state scenarios (no episodes)? [Coverage, Edge Case]"
- "Are concurrent user interaction scenarios addressed? [Coverage, Gap]"
- "Are requirements specified for partial data loading failures? [Coverage, Exception Flow]"
Measurability:
- "Are visual hierarchy requirements measurable/testable? [Acceptance Criteria, Spec §FR-1]"
- "Can 'balanced visual weight' be objectively verified? [Measurability, Spec §FR-2]"
Decision Memory:
- "Do all repo-shaping technical choices have explicit rationale before tasks are generated? [Decision Memory, Plan]"
- "Are rejected alternatives documented for architectural branches that would materially change implementation scope? [Decision Memory, Gap]"
- "Can a coder determine from the planning artifacts which tempting shortcut is forbidden? [Decision Memory, Clarity]"
**Scenario Classification & Coverage** (Requirements Quality Focus):
- Check if requirements exist for: Primary, Alternate, Exception/Error, Recovery, Non-Functional scenarios
- For each scenario class, ask: "Are [scenario type] requirements complete, clear, and consistent?"
- If scenario class missing: "Are [scenario type] requirements intentionally excluded or missing? [Gap]"
- Include resilience/rollback when state mutation occurs: "Are rollback requirements defined for migration failures? [Gap]"
**Traceability Requirements**:
- MINIMUM: ≥80% of items MUST include at least one traceability reference
- Each item should reference: spec section `[Spec §X.Y]`, or use markers: `[Gap]`, `[Ambiguity]`, `[Conflict]`, `[Assumption]`, `[ADR]`
- If no ID system exists: "Is a requirement & acceptance criteria ID scheme established? [Traceability]"
**Surface & Resolve Issues** (Requirements Quality Problems):
Ask questions about the requirements themselves:
- Ambiguities: "Is the term 'fast' quantified with specific metrics? [Ambiguity, Spec §NFR-1]"
- Conflicts: "Do navigation requirements conflict between §FR-10 and §FR-10a? [Conflict]"
- Assumptions: "Is the assumption of 'always available podcast API' validated? [Assumption]"
- Dependencies: "Are external podcast API requirements documented? [Dependency, Gap]"
- Missing definitions: "Is 'visual hierarchy' defined with measurable criteria? [Gap]"
- Decision-memory drift: "Do tasks inherit the same rejected-path guardrails defined in planning? [Decision Memory, Conflict]"
**Content Consolidation**:
- Soft cap: If raw candidate items > 40, prioritize by risk/impact
- Merge near-duplicates checking the same requirement aspect
- If >5 low-impact edge cases, create one item: "Are edge cases X, Y, Z addressed in requirements? [Coverage]"
**🚫 ABSOLUTELY PROHIBITED** - These make it an implementation test, not a requirements test:
- ❌ Any item starting with "Verify", "Test", "Confirm", "Check" + implementation behavior
- ❌ References to code execution, user actions, system behavior
- ❌ "Displays correctly", "works properly", "functions as expected"
- ❌ "Click", "navigate", "render", "load", "execute"
- ❌ Test cases, test plans, QA procedures
- ❌ Implementation details (frameworks, APIs, algorithms) unless the checklist is asking whether those decisions were explicitly documented and bounded by rationale/rejected alternatives
**✅ REQUIRED PATTERNS** - These test requirements quality:
- ✅ "Are [requirement type] defined/specified/documented for [scenario]?"
- ✅ "Is [vague term] quantified/clarified with specific criteria?"
- ✅ "Are requirements consistent between [section A] and [section B]?"
- ✅ "Can [requirement] be objectively measured/verified?"
- ✅ "Are [edge cases/scenarios] addressed in requirements?"
- ✅ "Does the spec define [missing aspect]?"
- ✅ "Does the plan record why [accepted path] was chosen and why [rejected path] is forbidden?"
6. **Structure Reference**: Generate the checklist following the canonical template in `.specify/templates/checklist-template.md` for title, meta section, category headings, and ID formatting. If template is unavailable, use: H1 title, purpose/created meta lines, `##` category sections containing `- [ ] CHK### <requirement item>` lines with globally incrementing IDs starting at CHK001.
7. **Report**: Output full path to created checklist, item count, and remind user that each run creates a new file. Summarize:
- Focus areas selected
- Depth level
- Actor/timing
- Any explicit user-specified must-have items incorporated
- Whether ADR / decision-memory checks were included
**Important**: Each `/speckit.checklist` command invocation creates a checklist file using short, descriptive names unless file already exists. This allows:
- Multiple checklists of different types (e.g., `ux.md`, `test.md`, `security.md`)
- Simple, memorable filenames that indicate checklist purpose
- Easy identification and navigation in the `checklists/` folder
To avoid clutter, use descriptive types and clean up obsolete checklists when done.
## Example Checklist Types & Sample Items
**UX Requirements Quality:** `ux.md`
Sample items (testing the requirements, NOT the implementation):
- "Are visual hierarchy requirements defined with measurable criteria? [Clarity, Spec §FR-1]"
- "Is the number and positioning of UI elements explicitly specified? [Completeness, Spec §FR-1]"
- "Are interaction state requirements (hover, focus, active) consistently defined? [Consistency]"
- "Are accessibility requirements specified for all interactive elements? [Coverage, Gap]"
- "Is fallback behavior defined when images fail to load? [Edge Case, Gap]"
- "Can 'prominent display' be objectively measured? [Measurability, Spec §FR-4]"
**API Requirements Quality:** `api.md`
Sample items:
- "Are error response formats specified for all failure scenarios? [Completeness]"
- "Are rate limiting requirements quantified with specific thresholds? [Clarity]"
- "Are authentication requirements consistent across all endpoints? [Consistency]"
- "Are retry/timeout requirements defined for external dependencies? [Coverage, Gap]"
- "Is versioning strategy documented in requirements? [Gap]"
**Performance Requirements Quality:** `performance.md`
Sample items:
- "Are performance requirements quantified with specific metrics? [Clarity]"
- "Are performance targets defined for all critical user journeys? [Coverage]"
- "Are performance requirements under different load conditions specified? [Completeness]"
- "Can performance requirements be objectively measured? [Measurability]"
- "Are degradation requirements defined for high-load scenarios? [Edge Case, Gap]"
**Security Requirements Quality:** `security.md`
Sample items:
- "Are authentication requirements specified for all protected resources? [Coverage]"
- "Are data protection requirements defined for sensitive information? [Completeness]"
- "Is the threat model documented and requirements aligned to it? [Traceability]"
- "Are security requirements consistent with compliance obligations? [Consistency]"
- "Are security failure/breach response requirements defined? [Gap, Exception Flow]"
**Architecture Decision Quality:** `architecture.md`
Sample items:
- "Do all repo-shaping architecture choices have explicit rationale before tasks are generated? [Decision Memory]"
- "Are rejected alternatives documented for each blocking technology branch? [Decision Memory, Gap]"
- "Can an implementer tell which shortcuts are forbidden without re-reading research artifacts? [Clarity, ADR]"
- "Are ADR decisions traceable to requirements or constraints in the spec? [Traceability, ADR]"
## Anti-Examples: What NOT To Do
**❌ WRONG - These test implementation, not requirements:**
```markdown
- [ ] CHK001 - Verify landing page displays 3 episode cards [Spec §FR-001]
- [ ] CHK002 - Test hover states work correctly on desktop [Spec §FR-003]
- [ ] CHK003 - Confirm logo click navigates to home page [Spec §FR-010]
- [ ] CHK004 - Check that related episodes section shows 3-5 items [Spec §FR-005]
```
**✅ CORRECT - These test requirements quality:**
```markdown
- [ ] CHK001 - Are the number and layout of featured episodes explicitly specified? [Completeness, Spec §FR-001]
- [ ] CHK002 - Are hover state requirements consistently defined for all interactive elements? [Consistency, Spec §FR-003]
- [ ] CHK003 - Are navigation requirements clear for all clickable brand elements? [Clarity, Spec §FR-010]
- [ ] CHK004 - Is the selection criteria for related episodes documented? [Gap, Spec §FR-005]
- [ ] CHK005 - Are loading state requirements defined for asynchronous episode data? [Gap]
- [ ] CHK006 - Can "visual hierarchy" requirements be objectively measured? [Measurability, Spec §FR-001]
- [ ] CHK007 - Do planning artifacts state why the accepted architecture was chosen and which alternative is rejected? [Decision Memory, ADR]
```
**Key Differences:**
- Wrong: Tests if the system works correctly
- Correct: Tests if the requirements are written correctly
- Wrong: Verification of behavior
- Correct: Validation of requirement quality
- Wrong: "Does it do X?"
- Correct: "Is X clearly specified?"

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---
description: Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
handoffs:
- label: Build Technical Plan
agent: speckit.plan
prompt: Create a plan for the spec. I am building with...
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
Goal: Detect and reduce ambiguity or missing decision points in the active feature specification and record the clarifications directly in the spec file.
Note: This clarification workflow is expected to run (and be completed) BEFORE invoking `/speckit.plan`. If the user explicitly states they are skipping clarification (e.g., exploratory spike), you may proceed, but must warn that downstream rework risk increases.
Execution steps:
1. Run `.specify/scripts/bash/check-prerequisites.sh --json --paths-only` from repo root **once** (combined `--json --paths-only` mode / `-Json -PathsOnly`). Parse minimal JSON payload fields:
- `FEATURE_DIR`
- `FEATURE_SPEC`
- (Optionally capture `IMPL_PLAN`, `TASKS` for future chained flows.)
- If JSON parsing fails, abort and instruct user to re-run `/speckit.specify` or verify feature branch environment.
- For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. Load the current spec file. Perform a structured ambiguity & coverage scan using this taxonomy. For each category, mark status: Clear / Partial / Missing. Produce an internal coverage map used for prioritization (do not output raw map unless no questions will be asked).
Functional Scope & Behavior:
- Core user goals & success criteria
- Explicit out-of-scope declarations
- User roles / personas differentiation
Domain & Data Model:
- Entities, attributes, relationships
- Identity & uniqueness rules
- Lifecycle/state transitions
- Data volume / scale assumptions
Interaction & UX Flow:
- Critical user journeys / sequences
- Error/empty/loading states
- Accessibility or localization notes
Non-Functional Quality Attributes:
- Performance (latency, throughput targets)
- Scalability (horizontal/vertical, limits)
- Reliability & availability (uptime, recovery expectations)
- Observability (logging, metrics, tracing signals)
- Security & privacy (authN/Z, data protection, threat assumptions)
- Compliance / regulatory constraints (if any)
Integration & External Dependencies:
- External services/APIs and failure modes
- Data import/export formats
- Protocol/versioning assumptions
Edge Cases & Failure Handling:
- Negative scenarios
- Rate limiting / throttling
- Conflict resolution (e.g., concurrent edits)
Constraints & Tradeoffs:
- Technical constraints (language, storage, hosting)
- Explicit tradeoffs or rejected alternatives
Terminology & Consistency:
- Canonical glossary terms
- Avoided synonyms / deprecated terms
Completion Signals:
- Acceptance criteria testability
- Measurable Definition of Done style indicators
Misc / Placeholders:
- TODO markers / unresolved decisions
- Ambiguous adjectives ("robust", "intuitive") lacking quantification
For each category with Partial or Missing status, add a candidate question opportunity unless:
- Clarification would not materially change implementation or validation strategy
- Information is better deferred to planning phase (note internally)
3. Generate (internally) a prioritized queue of candidate clarification questions (maximum 5). Do NOT output them all at once. Apply these constraints:
- Maximum of 10 total questions across the whole session.
- Each question must be answerable with EITHER:
- A short multiplechoice selection (25 distinct, mutually exclusive options), OR
- A one-word / shortphrase answer (explicitly constrain: "Answer in <=5 words").
- Only include questions whose answers materially impact architecture, data modeling, task decomposition, test design, UX behavior, operational readiness, or compliance validation.
- Ensure category coverage balance: attempt to cover the highest impact unresolved categories first; avoid asking two low-impact questions when a single high-impact area (e.g., security posture) is unresolved.
- Exclude questions already answered, trivial stylistic preferences, or plan-level execution details (unless blocking correctness).
- Favor clarifications that reduce downstream rework risk or prevent misaligned acceptance tests.
- If more than 5 categories remain unresolved, select the top 5 by (Impact * Uncertainty) heuristic.
4. Sequential questioning loop (interactive):
- Present EXACTLY ONE question at a time.
- For multiplechoice questions:
- **Analyze all options** and determine the **most suitable option** based on:
- Best practices for the project type
- Common patterns in similar implementations
- Risk reduction (security, performance, maintainability)
- Alignment with any explicit project goals or constraints visible in the spec
- Present your **recommended option prominently** at the top with clear reasoning (1-2 sentences explaining why this is the best choice).
- Format as: `**Recommended:** Option [X] - <reasoning>`
- Then render all options as a Markdown table:
| Option | Description |
|--------|-------------|
| A | <Option A description> |
| B | <Option B description> |
| C | <Option C description> (add D/E as needed up to 5) |
| Short | Provide a different short answer (<=5 words) (Include only if free-form alternative is appropriate) |
- After the table, add: `You can reply with the option letter (e.g., "A"), accept the recommendation by saying "yes" or "recommended", or provide your own short answer.`
- For shortanswer style (no meaningful discrete options):
- Provide your **suggested answer** based on best practices and context.
- Format as: `**Suggested:** <your proposed answer> - <brief reasoning>`
- Then output: `Format: Short answer (<=5 words). You can accept the suggestion by saying "yes" or "suggested", or provide your own answer.`
- After the user answers:
- If the user replies with "yes", "recommended", or "suggested", use your previously stated recommendation/suggestion as the answer.
- Otherwise, validate the answer maps to one option or fits the <=5 word constraint.
- If ambiguous, ask for a quick disambiguation (count still belongs to same question; do not advance).
- Once satisfactory, record it in working memory (do not yet write to disk) and move to the next queued question.
- Stop asking further questions when:
- All critical ambiguities resolved early (remaining queued items become unnecessary), OR
- User signals completion ("done", "good", "no more"), OR
- You reach 5 asked questions.
- Never reveal future queued questions in advance.
- If no valid questions exist at start, immediately report no critical ambiguities.
5. Integration after EACH accepted answer (incremental update approach):
- Maintain in-memory representation of the spec (loaded once at start) plus the raw file contents.
- For the first integrated answer in this session:
- Ensure a `## Clarifications` section exists (create it just after the highest-level contextual/overview section per the spec template if missing).
- Under it, create (if not present) a `### Session YYYY-MM-DD` subheading for today.
- Append a bullet line immediately after acceptance: `- Q: <question> → A: <final answer>`.
- Then immediately apply the clarification to the most appropriate section(s):
- Functional ambiguity → Update or add a bullet in Functional Requirements.
- User interaction / actor distinction → Update User Stories or Actors subsection (if present) with clarified role, constraint, or scenario.
- Data shape / entities → Update Data Model (add fields, types, relationships) preserving ordering; note added constraints succinctly.
- Non-functional constraint → Add/modify measurable criteria in Non-Functional / Quality Attributes section (convert vague adjective to metric or explicit target).
- Edge case / negative flow → Add a new bullet under Edge Cases / Error Handling (or create such subsection if template provides placeholder for it).
- Terminology conflict → Normalize term across spec; retain original only if necessary by adding `(formerly referred to as "X")` once.
- If the clarification invalidates an earlier ambiguous statement, replace that statement instead of duplicating; leave no obsolete contradictory text.
- Save the spec file AFTER each integration to minimize risk of context loss (atomic overwrite).
- Preserve formatting: do not reorder unrelated sections; keep heading hierarchy intact.
- Keep each inserted clarification minimal and testable (avoid narrative drift).
6. Validation (performed after EACH write plus final pass):
- Clarifications session contains exactly one bullet per accepted answer (no duplicates).
- Total asked (accepted) questions ≤ 5.
- Updated sections contain no lingering vague placeholders the new answer was meant to resolve.
- No contradictory earlier statement remains (scan for now-invalid alternative choices removed).
- Markdown structure valid; only allowed new headings: `## Clarifications`, `### Session YYYY-MM-DD`.
- Terminology consistency: same canonical term used across all updated sections.
7. Write the updated spec back to `FEATURE_SPEC`.
8. Report completion (after questioning loop ends or early termination):
- Number of questions asked & answered.
- Path to updated spec.
- Sections touched (list names).
- Coverage summary table listing each taxonomy category with Status: Resolved (was Partial/Missing and addressed), Deferred (exceeds question quota or better suited for planning), Clear (already sufficient), Outstanding (still Partial/Missing but low impact).
- If any Outstanding or Deferred remain, recommend whether to proceed to `/speckit.plan` or run `/speckit.clarify` again later post-plan.
- Suggested next command.
Behavior rules:
- If no meaningful ambiguities found (or all potential questions would be low-impact), respond: "No critical ambiguities detected worth formal clarification." and suggest proceeding.
- If spec file missing, instruct user to run `/speckit.specify` first (do not create a new spec here).
- Never exceed 5 total asked questions (clarification retries for a single question do not count as new questions).
- Avoid speculative tech stack questions unless the absence blocks functional clarity.
- Respect user early termination signals ("stop", "done", "proceed").
- If no questions asked due to full coverage, output a compact coverage summary (all categories Clear) then suggest advancing.
- If quota reached with unresolved high-impact categories remaining, explicitly flag them under Deferred with rationale.
Context for prioritization: $ARGUMENTS

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---
description: Create or update the project constitution from interactive or provided principle inputs, ensuring all dependent templates stay in sync.
handoffs:
- label: Build Specification
agent: speckit.specify
prompt: Implement the feature specification based on the updated constitution. I want to build...
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
You are updating the project constitution at `.ai/standards/constitution.md`. This file is a TEMPLATE containing placeholder tokens in square brackets (e.g. `[PROJECT_NAME]`, `[PRINCIPLE_1_NAME]`). Your job is to (a) collect/derive concrete values, (b) fill the template precisely, and (c) propagate any amendments across dependent artifacts.
Follow this execution flow:
1. Load the existing constitution template at `.ai/standards/constitution.md`.
- Identify every placeholder token of the form `[ALL_CAPS_IDENTIFIER]`.
**IMPORTANT**: The user might require less or more principles than the ones used in the template. If a number is specified, respect that - follow the general template. You will update the doc accordingly.
2. Collect/derive values for placeholders:
- If user input (conversation) supplies a value, use it.
- Otherwise infer from existing repo context (README, docs, prior constitution versions if embedded).
- For governance dates: `RATIFICATION_DATE` is the original adoption date (if unknown ask or mark TODO), `LAST_AMENDED_DATE` is today if changes are made, otherwise keep previous.
- `CONSTITUTION_VERSION` must increment according to semantic versioning rules:
- MAJOR: Backward incompatible governance/principle removals or redefinitions.
- MINOR: New principle/section added or materially expanded guidance.
- PATCH: Clarifications, wording, typo fixes, non-semantic refinements.
- If version bump type ambiguous, propose reasoning before finalizing.
3. Draft the updated constitution content:
- Replace every placeholder with concrete text (no bracketed tokens left except intentionally retained template slots that the project has chosen not to define yet—explicitly justify any left).
- Preserve heading hierarchy and comments can be removed once replaced unless they still add clarifying guidance.
- Ensure each Principle section: succinct name line, paragraph (or bullet list) capturing nonnegotiable rules, explicit rationale if not obvious.
- Ensure Governance section lists amendment procedure, versioning policy, and compliance review expectations.
4. Consistency propagation checklist (convert prior checklist into active validations):
- Read `.specify/templates/plan-template.md` and ensure any "Constitution Check" or rules align with updated principles.
- Read `.specify/templates/spec-template.md` for scope/requirements alignment—update if constitution adds/removes mandatory sections or constraints.
- Read `.specify/templates/tasks-template.md` and ensure task categorization reflects new or removed principle-driven task types (e.g., observability, versioning, testing discipline).
- Read each command file in `.specify/templates/commands/*.md` (including this one) to verify no outdated references (agent-specific names like CLAUDE only) remain when generic guidance is required.
- Read any runtime guidance docs (e.g., `README.md`, `docs/quickstart.md`, or agent-specific guidance files if present). Update references to principles changed.
5. Produce a Sync Impact Report (prepend as an HTML comment at top of the constitution file after update):
- Version change: old → new
- List of modified principles (old title → new title if renamed)
- Added sections
- Removed sections
- Templates requiring updates (✅ updated / ⚠ pending) with file paths
- Follow-up TODOs if any placeholders intentionally deferred.
6. Validation before final output:
- No remaining unexplained bracket tokens.
- Version line matches report.
- Dates ISO format YYYY-MM-DD.
- Principles are declarative, testable, and free of vague language ("should" → replace with MUST/SHOULD rationale where appropriate).
7. Write the completed constitution back to `.ai/standards/constitution.md` (overwrite).
8. Output a final summary to the user with:
- New version and bump rationale.
- Any files flagged for manual follow-up.
- Suggested commit message (e.g., `docs: amend constitution to vX.Y.Z (principle additions + governance update)`).
Formatting & Style Requirements:
- Use Markdown headings exactly as in the template (do not demote/promote levels).
- Wrap long rationale lines to keep readability (<100 chars ideally) but do not hard enforce with awkward breaks.
- Keep a single blank line between sections.
- Avoid trailing whitespace.
If the user supplies partial updates (e.g., only one principle revision), still perform validation and version decision steps.
If critical info missing (e.g., ratification date truly unknown), insert `TODO(<FIELD_NAME>): explanation` and include in the Sync Impact Report under deferred items.
Do not create a new template; always operate on the existing `.ai/standards/constitution.md` file.

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---
description: Execute the implementation plan by processing and executing all tasks defined in tasks.md
handoffs:
- label: Audit & Verify (Tester)
agent: tester
prompt: Perform semantic audit, algorithm emulation, and unit test verification for the completed tasks.
send: true
- label: Orchestration Control
agent: orchestrator
prompt: Review Tester's feedback and coordinate next steps.
send: true
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. Run `.specify/scripts/bash/check-prerequisites.sh --json --require-tasks --include-tasks` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Check checklists status** (if FEATURE_DIR/checklists/ exists):
- Scan all checklist files in the checklists/ directory
- For each checklist, count:
- Total items: All lines matching `- [ ]` or `- [X]` or `- [x]`
- Completed items: Lines matching `- [X]` or `- [x]`
- Incomplete items: Lines matching `- [ ]`
- Create a status table:
```text
| Checklist | Total | Completed | Incomplete | Status |
|-----------|-------|-----------|------------|--------|
| ux.md | 12 | 12 | 0 | ✓ PASS |
| test.md | 8 | 5 | 3 | ✗ FAIL |
| security.md | 6 | 6 | 0 | ✓ PASS |
```
- Calculate overall status:
- **PASS**: All checklists have 0 incomplete items
- **FAIL**: One or more checklists have incomplete items
- **If any checklist is incomplete**:
- Display the table with incomplete item counts
- **STOP** and ask: "Some checklists are incomplete. Do you want to proceed with implementation anyway? (yes/no)"
- Wait for user response before continuing
- If user says "no" or "wait" or "stop", halt execution
- If user says "yes" or "proceed" or "continue", proceed to step 3
- **If all checklists are complete**:
- Display the table showing all checklists passed
- Automatically proceed to step 3
3. Load and analyze the implementation context:
- **REQUIRED**: Read `.ai/standards/semantics.md` for strict coding standards and contract requirements
- **REQUIRED**: Read `tasks.md` for the complete task list and execution plan
- **REQUIRED**: Read `plan.md` for tech stack, architecture, and file structure
- **REQUIRED IF PRESENT**: Read ADR artifacts containing `[DEF:id:ADR]` nodes and build a blocked-path inventory from `@REJECTED`
- **IF EXISTS**: Read `data-model.md` for entities and relationships
- **IF EXISTS**: Read `contracts/` for API specifications and test requirements
- **IF EXISTS**: Read `research.md` for technical decisions and constraints
- **IF EXISTS**: Read `quickstart.md` for integration scenarios
4. **Project Setup Verification**:
- **REQUIRED**: Create/verify ignore files based on actual project setup:
**Detection & Creation Logic**:
- Check if the following command succeeds to determine if the repository is a git repo (create/verify `.gitignore` if so):
```sh
git rev-parse --git-dir 2>/dev/null
```
- Check if Dockerfile* exists or Docker in `plan.md` → create/verify `.dockerignore`
- Check if `.eslintrc*` exists → create/verify `.eslintignore`
- Check if `eslint.config.*` exists → ensure the config's `ignores` entries cover required patterns
- Check if `.prettierrc*` exists → create/verify `.prettierignore`
- Check if `.npmrc` or `package.json` exists → create/verify `.npmignore` (if publishing)
- Check if terraform files (`*.tf`) exist → create/verify `.terraformignore`
- Check if `.helmignore` needed (helm charts present) → create/verify `.helmignore`
**If ignore file already exists**: Verify it contains essential patterns, append missing critical patterns only
**If ignore file missing**: Create with full pattern set for detected technology
**Common Patterns by Technology** (from `plan.md` tech stack):
- **Node.js/JavaScript/TypeScript**: `node_modules/`, `dist/`, `build/`, `*.log`, `.env*`
- **Python**: `__pycache__/`, `*.pyc`, `.venv/`, `venv/`, `dist/`, `*.egg-info/`
- **Java**: `target/`, `*.class`, `*.jar`, `.gradle/`, `build/`
- **C#/.NET**: `bin/`, `obj/`, `*.user`, `*.suo`, `packages/`
- **Go**: `*.exe`, `*.test`, `vendor/`, `*.out`
- **Ruby**: `.bundle/`, `log/`, `tmp/`, `*.gem`, `vendor/bundle/`
- **PHP**: `vendor/`, `*.log`, `*.cache`, `*.env`
- **Rust**: `target/`, `debug/`, `release/`, `*.rs.bk`, `*.rlib`, `*.prof*`, `.idea/`, `*.log`, `.env*`
- **Kotlin**: `build/`, `out/`, `.gradle/`, `.idea/`, `*.class`, `*.jar`, `*.iml`, `*.log`, `.env*`
- **C++**: `build/`, `bin/`, `obj/`, `out/`, `*.o`, `*.so`, `*.a`, `*.exe`, `*.dll`, `.idea/`, `*.log`, `.env*`
- **C**: `build/`, `bin/`, `obj/`, `out/`, `*.o`, `*.a`, `*.so`, `*.exe`, `Makefile`, `config.log`, `.idea/`, `*.log`, `.env*`
- **Swift**: `.build/`, `DerivedData/`, `*.swiftpm/`, `Packages/`
- **R**: `.Rproj.user/`, `.Rhistory`, `.RData`, `.Ruserdata`, `*.Rproj`, `packrat/`, `renv/`
- **Universal**: `.DS_Store`, `Thumbs.db`, `*.tmp`, `*.swp`, `.vscode/`, `.idea/`
**Tool-Specific Patterns**:
- **Docker**: `node_modules/`, `.git/`, `Dockerfile*`, `.dockerignore`, `*.log*`, `.env*`, `coverage/`
- **ESLint**: `node_modules/`, `dist/`, `build/`, `coverage/`, `*.min.js`
- **Prettier**: `node_modules/`, `dist/`, `build/`, `coverage/`, `package-lock.json`, `yarn.lock`, `pnpm-lock.yaml`
- **Terraform**: `.terraform/`, `*.tfstate*`, `*.tfvars`, `.terraform.lock.hcl`
- **Kubernetes/k8s**: `*.secret.yaml`, `secrets/`, `.kube/`, `kubeconfig*`, `*.key`, `*.crt`
5. Parse `tasks.md` structure and extract:
- **Task phases**: Setup, Tests, Core, Integration, Polish
- **Task dependencies**: Sequential vs parallel execution rules
- **Task details**: ID, description, file paths, parallel markers [P]
- **Execution flow**: Order and dependency requirements
- **Decision-memory requirements**: which tasks inherit ADR ids, `@RATIONALE`, and `@REJECTED` guardrails
6. Execute implementation following the task plan:
- **Phase-by-phase execution**: Complete each phase before moving to the next
- **Respect dependencies**: Run sequential tasks in order, parallel tasks [P] can run together
- **Follow TDD approach**: Execute test tasks before their corresponding implementation tasks
- **File-based coordination**: Tasks affecting the same files must run sequentially
- **Validation checkpoints**: Verify each phase completion before proceeding
- **ADR guardrail discipline**: if a task packet or local contract forbids a path via `@REJECTED`, do not treat it as an implementation option
7. Implementation execution rules:
- **Strict Adherence**: Apply `.ai/standards/semantics.md` rules:
- Every file MUST start with a `[DEF:id:Type]` header and end with a matching closing `[/DEF:id:Type]` anchor.
- Use `@COMPLEXITY` / `@C:` as the primary control tag; treat `@TIER` only as legacy compatibility metadata.
- Contract density MUST match effective complexity from [`.ai/standards/semantics.md`](.ai/standards/semantics.md):
- Complexity 1: anchors only.
- Complexity 2: require `@PURPOSE`.
- Complexity 3: require `@PURPOSE` and `@RELATION`.
- Complexity 4: require `@PURPOSE`, `@RELATION`, `@PRE`, `@POST`, `@SIDE_EFFECT`.
- Complexity 5: require full level-4 contract plus `@DATA_CONTRACT` and `@INVARIANT`.
- For Python Complexity 4+ modules, implementation MUST include a meaningful semantic logging path using `logger.reason()` and `logger.reflect()`.
- For Python Complexity 5 modules, `belief_scope(...)` is mandatory and the critical path must be irrigated with `logger.reason()` / `logger.reflect()` according to the contract.
- For Svelte components, require `@UX_STATE`, `@UX_FEEDBACK`, `@UX_RECOVERY`, and `@UX_REACTIVITY`; runes-only reactivity is allowed (`$state`, `$derived`, `$effect`, `$props`).
- Reject pseudo-semantic markup: docstrings containing loose `@PURPOSE` / `@PRE` text do **NOT** satisfy the protocol unless represented in canonical anchored metadata blocks.
- Preserve and propagate decision-memory tags. Upstream `@RATIONALE` / `@REJECTED` are mandatory when carried by the task packet or contract.
- If `logger.explore()` or equivalent runtime evidence leads to a retained workaround, mutate the same contract header with reactive Micro-ADR tags: `@RATIONALE` and `@REJECTED`.
- **Self-Audit**: The Coder MUST use `axiom-core` tools (like `audit_contracts_tool`) to verify semantic compliance before completion.
- **Semantic Rejection Gate**: If self-audit reveals broken anchors, missing closing tags, missing required metadata for the effective complexity, orphaned critical classes/functions, Complexity 4/5 Python code without required belief-state logging, or retained workarounds without decision-memory tags, the task is NOT complete and cannot be handed off as accepted work.
- **CRITICAL Contracts**: If a task description contains a contract summary (e.g., `CRITICAL: PRE: ..., POST: ...`), these constraints are **MANDATORY** and must be strictly implemented in the code using guards/assertions (if applicable per protocol).
- **Setup first**: Initialize project structure, dependencies, configuration
- **Tests before code**: If you need to write tests for contracts, entities, and integration scenarios
- **Core development**: Implement models, services, CLI commands, endpoints
- **Integration work**: Database connections, middleware, logging, external services
- **Polish and validation**: Unit tests, performance optimization, documentation
8. Progress tracking and error handling:
- Report progress after each completed task.
- Halt execution if any non-parallel task fails.
- For parallel tasks [P], continue with successful tasks, report failed ones.
- Provide clear error messages with context for debugging.
- Suggest next steps if implementation cannot proceed.
- **IMPORTANT** For completed tasks, mark as [X] only AFTER local verification and self-audit.
- If blocked because the only apparent fix is listed in upstream `@REJECTED`, escalate for decision revision instead of silently overriding the guardrail.
9. **Handoff to Tester (Audit Loop)**:
- Once a task or phase is complete, the Coder hands off to the Tester.
- Handoff includes: file paths, declared complexity, expected contracts (`@PRE`, `@POST`, `@SIDE_EFFECT`, `@DATA_CONTRACT`, `@INVARIANT` when applicable), and a short logic overview.
- Handoff MUST explicitly disclose any contract exceptions or known semantic debt. Hidden semantic debt is forbidden.
- Handoff MUST disclose decision-memory changes: inherited ADR ids, new or updated `@RATIONALE`, new or updated `@REJECTED`, and any blocked paths that remain active.
- The handoff payload MUST instruct the Tester to execute the dedicated testing workflow [`.kilocode/workflows/speckit.test.md`](.kilocode/workflows/speckit.test.md), not just perform an informal review.
10. **Tester Verification & Orchestrator Gate**:
- Tester MUST:
- Explicitly run the [`.kilocode/workflows/speckit.test.md`](.kilocode/workflows/speckit.test.md) workflow as the verification procedure for the delivered implementation batch.
- Perform mandatory semantic audit (using `audit_contracts_tool`).
- Reject code that only imitates the protocol superficially, such as free-form docstrings with `@PURPOSE` text but without canonical `[DEF]...[/DEF]` anchors and header metadata.
- Verify that effective complexity and required metadata match [`.ai/standards/semantics.md`](.ai/standards/semantics.md).
- Verify that Python Complexity 4/5 implementations include required belief-state instrumentation (`belief_scope`, `logger.reason()`, `logger.reflect()`).
- Verify that upstream rejected paths were not silently restored.
- Emulate algorithms "in mind" step-by-step to ensure logic consistency.
- Verify unit tests match the declared contracts.
- If Tester finds issues:
- Emit `[AUDIT_FAIL: semantic_noncompliance | contract_mismatch | logic_mismatch | test_mismatch | speckit_test_not_run | rejected_path_regression]`.
- Provide concrete file-path-based reasons, for example: missing anchors, module/class contract mismatch, missing `@DATA_CONTRACT`, missing `logger.reason()`, illegal docstring-only annotations, missing decision-memory tags, re-enabled upstream rejected path, or missing execution of [`.kilocode/workflows/speckit.test.md`](.kilocode/workflows/speckit.test.md).
- Notify the Orchestrator.
- Orchestrator redirects the feedback to the Coder for remediation.
- Orchestrator green-status rule:
- The Orchestrator MUST NOT assign green/accepted status unless the Tester confirms that [`.kilocode/workflows/speckit.test.md`](.kilocode/workflows/speckit.test.md) was executed.
- Missing execution evidence for [`.kilocode/workflows/speckit.test.md`](.kilocode/workflows/speckit.test.md) is an automatic gate failure even if the Tester verbally reports that the code "looks fine".
- Acceptance (Final mark [X]):
- Only after the Tester is satisfied with semantics, emulation, and tests.
- Any semantic audit warning relevant to touched files blocks acceptance until remediated or explicitly waived by the user.
- No final green status is allowed without explicit confirmation that [`.kilocode/workflows/speckit.test.md`](.kilocode/workflows/speckit.test.md) was run.
11. Completion validation:
- Verify all required tasks are completed and accepted by the Tester.
- Check that implemented features match the original specification.
- Confirm the implementation follows the technical plan and GRACE standards.
- Confirm touched files do not contain protocol-invalid patterns such as:
- class/function-level docstring contracts standing in for canonical anchors,
- missing closing anchors,
- missing required metadata for declared complexity,
- Complexity 5 repository/service code using only `belief_scope(...)` without explicit `logger.reason()` / `logger.reflect()` checkpoints,
- retained workarounds missing local `@RATIONALE` / `@REJECTED`,
- silent resurrection of paths already blocked by upstream ADR or task guardrails.
- Report final status with summary of completed and audited work.
Note: This command assumes a complete task breakdown exists in `tasks.md`. If tasks are incomplete or missing, suggest running `/speckit.tasks` first to regenerate the task list.

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---
description: Execute the implementation planning workflow using the plan template to generate design artifacts.
handoffs:
- label: Create Tasks
agent: speckit.tasks
prompt: Break the plan into tasks
send: true
- label: Create Checklist
agent: speckit.checklist
prompt: Create a checklist for the following domain...
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. **Setup**: Run `.specify/scripts/bash/setup-plan.sh --json` from repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Load context**: Read `.ai/ROOT.md` and `.ai/PROJECT_MAP.md` to understand the project structure and navigation. Then read required standards: `.ai/standards/constitution.md` and `.ai/standards/semantics.md`. Load IMPL_PLAN template.
3. **Execute plan workflow**: Follow the structure in IMPL_PLAN template to:
- Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
- Fill Constitution Check section from constitution
- Evaluate gates (ERROR if violations unjustified)
- Phase 0: Generate `research.md` (resolve all NEEDS CLARIFICATION)
- Phase 1: Generate `data-model.md`, `contracts/`, `quickstart.md`
- Phase 1: Generate global ADR artifacts and connect them to the plan
- Phase 1: Update agent context by running the agent script
- Re-evaluate Constitution Check post-design
4. **Stop and report**: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, generated artifacts, and ADR decisions created.
## Phases
### Phase 0: Outline & Research
1. **Extract unknowns from Technical Context** above:
- For each NEEDS CLARIFICATION → research task
- For each dependency → best practices task
- For each integration → patterns task
2. **Generate and dispatch research agents**:
```text
For each unknown in Technical Context:
Task: "Research {unknown} for {feature context}"
For each technology choice:
Task: "Find best practices for {tech} in {domain}"
```
3. **Consolidate findings** in `research.md` using format:
- Decision: [what was chosen]
- Rationale: [why chosen]
- Alternatives considered: [what else evaluated]
**Output**: `research.md` with all NEEDS CLARIFICATION resolved
### Phase 1: Design, ADRs & Contracts
**Prerequisites:** `research.md` complete
0. **Validate Design against UX Reference**:
- Check if the proposed architecture supports the latency, interactivity, and flow defined in `ux_reference.md`.
- **Linkage**: Ensure key UI states from `ux_reference.md` map to Component Contracts (`@UX_STATE`).
- **CRITICAL**: If the technical plan compromises the UX (e.g. "We can't do real-time validation"), you **MUST STOP** and warn the user.
1. **Extract entities from feature spec** → `data-model.md`:
- Entity name, fields, relationships, validation rules.
2. **Generate Global ADRs (Decision Memory Root Layer)**:
- Read `spec.md`, `research.md`, and the technical context to identify repo-shaping decisions: storage, auth pattern, framework boundaries, integration patterns, deployment assumptions, failure strategy.
- For each durable architectural choice, emit a standalone semantic ADR block using `[DEF:DecisionId:ADR]`.
- Every ADR block MUST include:
- `@COMPLEXITY: 3` or `4` depending on blast radius
- `@PURPOSE`
- `@RATIONALE`
- `@REJECTED`
- `@RELATION` back to the originating spec/research/plan boundary or target module family
- Preferred destinations:
- `docs/architecture.md` for cross-cutting repository decisions
- feature-local design docs when the decision is feature-scoped
- root module headers only when the decision scope is truly local
- **Hard Gate**: do not continue to task decomposition until the blocking global decisions have been materialized as ADR nodes.
- **Anti-Regression Goal**: a later orchestrator must be able to read these ADRs and avoid creating tasks for rejected branches.
3. **Design & Verify Contracts (Semantic Protocol)**:
- **Drafting**: Define semantic headers, metadata, and closing anchors for all new modules strictly from `.ai/standards/semantics.md`.
- **Complexity Classification**: Classify each contract with `@COMPLEXITY: [1|2|3|4|5]` or `@C:`. Treat `@TIER` only as a legacy compatibility hint and never as the primary rule source.
- **Adaptive Contract Requirements**:
- **Complexity 1**: anchors only; `@PURPOSE` optional.
- **Complexity 2**: require `@PURPOSE`.
- **Complexity 3**: require `@PURPOSE` and `@RELATION`; UI also requires `@UX_STATE`.
- **Complexity 4**: require `@PURPOSE`, `@RELATION`, `@PRE`, `@POST`, `@SIDE_EFFECT`; Python modules must define a meaningful `logger.reason()` / `logger.reflect()` path or equivalent belief-state mechanism.
- **Complexity 5**: require full level-4 contract plus `@DATA_CONTRACT` and `@INVARIANT`; Python modules must require `belief_scope`; UI modules must define UX contracts including `@UX_STATE`, `@UX_FEEDBACK`, `@UX_RECOVERY`, and `@UX_REACTIVITY`.
- **Decision-Memory Propagation**:
- If a module/function/component realizes or is constrained by an ADR, add local `@RATIONALE` and `@REJECTED` guardrails before coding begins.
- Use `@RELATION: IMPLEMENTS ->[AdrId]` when the contract realizes the ADR.
- Use `@RELATION: DEPENDS_ON ->[AdrId]` when the contract is merely constrained by the ADR.
- Record known LLM traps directly in the contract header so the implementer inherits the guardrail from the start.
- **Relation Syntax**: Write dependency edges in canonical GraphRAG form: `@RELATION: [PREDICATE] ->[TARGET_ID]`.
- **Context Guard**: If a target relation, DTO, required dependency, or decision rationale cannot be named confidently, stop generation and emit `[NEED_CONTEXT: target]` instead of inventing placeholders.
- **Testing Contracts**: Add `@TEST_CONTRACT`, `@TEST_SCENARIO`, `@TEST_FIXTURE`, `@TEST_EDGE`, and `@TEST_INVARIANT` when the design introduces audit-critical or explicitly test-governed contracts, especially for Complexity 5 boundaries.
- **Self-Review**:
- *Complexity Fit*: Does each contract include exactly the metadata and contract density required by its complexity level?
- *Completeness*: Do `@PRE`/`@POST`, `@SIDE_EFFECT`, `@DATA_CONTRACT`, UX tags, and decision-memory tags cover the edge cases identified in Research and UX Reference?
- *Connectivity*: Do `@RELATION` tags form a coherent graph using canonical `@RELATION: [PREDICATE] ->[TARGET_ID]` syntax?
- *Compliance*: Are all anchors properly opened and closed, and does the chosen comment syntax match the target medium?
- *Belief-State Requirements*: Do Complexity 4/5 Python modules explicitly account for `logger.reason()`, `logger.reflect()`, and `belief_scope` requirements?
- *ADR Continuity*: Does every blocking architectural decision have a corresponding ADR node and at least one downstream guarded contract?
- **Output**: Write verified contracts to `contracts/modules.md`.
4. **Simulate Contract Usage**:
- Trace one key user scenario through the defined contracts to ensure data flow continuity.
- If a contract interface mismatch is found, fix it immediately.
- Verify that no traced path accidentally realizes an alternative already named in any ADR `@REJECTED` tag.
5. **Generate API contracts**:
- Output OpenAPI/GraphQL schema to `/contracts/` for backend-frontend sync.
6. **Agent context update**:
- Run `.specify/scripts/bash/update-agent-context.sh kilocode`
- These scripts detect which AI agent is in use
- Update the appropriate agent-specific context file
- Add only new technology from current plan
- Preserve manual additions between markers
**Output**: `data-model.md`, `/contracts/*`, `quickstart.md`, ADR artifact(s), agent-specific file
## Key rules
- Use absolute paths
- ERROR on gate failures or unresolved clarifications
- Do not hand off to [`speckit.tasks`](.kilocode/workflows/speckit.tasks.md) until blocking ADRs exist and rejected branches are explicit

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---
description: Maintain semantic integrity by generating maps and auditing compliance reports.
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Goal
Ensure the codebase adheres to the semantic standards defined in `.ai/standards/semantics.md` by using the AXIOM MCP semantic graph as the primary execution engine. This involves reindexing the workspace, measuring semantic health, auditing contract compliance, auditing decision-memory continuity, and optionally delegating contract-safe fixes through MCP-aware agents.
## Operating Constraints
1. **ROLE: Orchestrator**: You are responsible for the high-level coordination of semantic maintenance.
2. **MCP-FIRST**: Use the connected AXIOM MCP server as the default mechanism for discovery, health checks, audit, semantic context, impact analysis, and contract mutation planning.
3. **STRICT ADHERENCE**: Follow `.ai/standards/semantics.md` for all anchor and tag syntax.
4. **NON-DESTRUCTIVE**: Do not remove existing code logic; only add or update semantic annotations.
5. **TIER AWARENESS**: Prioritize CRITICAL and STANDARD modules for compliance fixes.
6. **NO PSEUDO-CONTRACTS (CRITICAL)**: You are STRICTLY FORBIDDEN from using automated scripts (e.g., Python/Bash/sed) to mechanically inject boilerplate, placeholders, or "pseudo-contracts" merely to artificially inflate the compliance score. Every semantic tag, anchor, and contract you add MUST reflect a genuine, deep understanding of the code's actual logic and business requirements.
7. **ID NAMING (CRITICAL)**: NEVER use fully-qualified Python import paths in `[DEF:id:Type]`. Use short, domain-driven semantic IDs (e.g., `[DEF:AuthService:Class]`). Follow the exact style shown in `.ai/standards/semantics.md`.
8. **ORPHAN PREVENTION**: To reduce the orphan count, you MUST physically wrap actual class and function definitions with `[DEF:id:Type] ... [/DEF]` blocks in the code. Modifying `@RELATION` tags does NOT fix orphans. The AST parser flags any unwrapped function as an orphan.
- **Exception for Tests**: In test modules, use `BINDS_TO` to link major helpers to the module root. Small helpers remain C1 and don't need relations.
9. **DECISION-MEMORY CONTINUITY**: Audit ADR nodes, preventive task guardrails, and reactive Micro-ADR tags as one anti-regression chain. Missing or contradictory `@RATIONALE` / `@REJECTED` is a first-class semantic defect.
## Execution Steps
### 1. Reindex Semantic Workspace
Use MCP to refresh the semantic graph for the current workspace with [`reindex_workspace_tool`](.kilo/mcp.json).
### 2. Analyze Semantic Health
Use [`workspace_semantic_health_tool`](.kilo/mcp.json) and capture:
- `contracts`
- `relations`
- `orphans`
- `unresolved_relations`
- `files`
Treat high orphan counts and unresolved relations as first-class health indicators, not just informational noise.
### 3. Audit Critical Issues
Use [`audit_contracts_tool`](.kilo/mcp.json) and classify findings into:
- **Critical Parsing/Structure Errors**: malformed or incoherent semantic contract regions
- **Critical Contract Gaps**: missing [`@DATA_CONTRACT`](.ai/standards/semantics.md), [`@PRE`](.ai/standards/semantics.md), [`@POST`](.ai/standards/semantics.md), [`@SIDE_EFFECT`](.ai/standards/semantics.md) on CRITICAL contracts
- **Decision-Memory Gaps**:
- missing standalone `[DEF:id:ADR]` for repo-shaping decisions
- missing `@RATIONALE` / `@REJECTED` where task or implementation context clearly requires guardrails
- retained workaround code without local reactive Micro-ADR tags
- implementation that silently re-enables a path declared in upstream `@REJECTED`
- **Coverage Gaps**: missing [`@TIER`](.ai/standards/semantics.md), missing [`@PURPOSE`](.ai/standards/semantics.md)
- **Graph Breakages**: unresolved relations, broken references, isolated critical contracts, ADR nodes without downstream guarded contracts
### 4. Build Remediation Context
For the top failing contracts, use MCP semantic context tools such as [`get_semantic_context_tool`](.kilo/mcp.json), [`build_task_context_tool`](.kilo/mcp.json), [`impact_analysis_tool`](.kilo/mcp.json), and [`trace_tests_for_contract_tool`](.kilo/mcp.json) to understand:
1. Local contract intent
2. Upstream/downstream semantic impact
3. Related tests and fixtures
4. Whether relation recovery is needed
5. Whether decision-memory continuity is broken between ADR, task contract, and implementation
### 5. Execute Fixes (Optional/Handoff)
If $ARGUMENTS contains `fix` or `apply`:
- Handoff to the [`semantic`](.kilocodemodes) mode or a dedicated implementation agent instead of applying naive textual edits in orchestration.
- Require the fixing agent to prefer MCP contract mutation tools such as [`simulate_patch_tool`](.kilo/mcp.json), [`guarded_patch_contract_tool`](.kilo/mcp.json), [`patch_contract_tool`](.kilo/mcp.json), and [`infer_missing_relations_tool`](.kilo/mcp.json).
- Require the fixing agent to preserve or restore `@RATIONALE` / `@REJECTED` continuity whenever blocked-path knowledge exists.
- After changes, re-run reindex, health, and audit MCP steps to verify the delta.
### 6. Review Gate
Before completion, request or perform an MCP-based review path aligned with the [`reviewer-agent-auditor`](.kilocodemodes) mode so the workflow produces a semantic PASS/FAIL gate, not just a remediation list.
## Output
Provide a summary of the semantic state:
- **Health Metrics**: contracts / relations / orphans / unresolved_relations / files
- **Status**: [PASS/FAIL] (FAIL if CRITICAL gaps, rejected-path regressions, or semantically significant unresolved relations exist)
- **Top Issues**: List top 3-5 contracts or files needing attention.
- **Decision Memory**: summarize missing ADRs, missing guardrails, and rejected-path regression risks.
- **Action Taken**: Summary of MCP analysis performed, context gathered, and fixes or handoffs initiated.
## Context
$ARGUMENTS

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---
description: Create or update the feature specification from a natural language feature description.
handoffs:
- label: Build Technical Plan
agent: speckit.plan
prompt: Create a plan for the spec. I am building with...
- label: Clarify Spec Requirements
agent: speckit.clarify
prompt: Clarify specification requirements
send: true
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
The text the user typed after `/speckit.specify` in the triggering message **is** the feature description. Assume you always have it available in this conversation even if `$ARGUMENTS` appears literally below. Do not ask the user to repeat it unless they provided an empty command.
Given that feature description, do this:
1. **Generate a concise short name** (2-4 words) for the branch:
- Analyze the feature description and extract the most meaningful keywords
- Create a 2-4 word short name that captures the essence of the feature
- Use action-noun format when possible (e.g., "add-user-auth", "fix-payment-bug")
- Preserve technical terms and acronyms (OAuth2, API, JWT, etc.)
- Keep it concise but descriptive enough to understand the feature at a glance
- Examples:
- "I want to add user authentication" → "user-auth"
- "Implement OAuth2 integration for the API" → "oauth2-api-integration"
- "Create a dashboard for analytics" → "analytics-dashboard"
- "Fix payment processing timeout bug" → "fix-payment-timeout"
2. **Check for existing branches before creating new one**:
a. First, fetch all remote branches to ensure we have the latest information:
```bash
git fetch --all --prune
```
b. Find the highest feature number across all sources for the short-name:
- Remote branches: `git ls-remote --heads origin | grep -E 'refs/heads/[0-9]+-<short-name>$'`
- Local branches: `git branch | grep -E '^[* ]*[0-9]+-<short-name>$'`
- Specs directories: Check for directories matching `specs/[0-9]+-<short-name>`
c. Determine the next available number:
- Extract all numbers from all three sources
- Find the highest number N
- Use N+1 for the new branch number
d. Run the script `.specify/scripts/bash/create-new-feature.sh --json "$ARGUMENTS"` with the calculated number and short-name:
- Pass `--number N+1` and `--short-name "your-short-name"` along with the feature description
- Bash example: `.specify/scripts/bash/create-new-feature.sh --json "$ARGUMENTS" --json --number 5 --short-name "user-auth" "Add user authentication"`
- PowerShell example: `.specify/scripts/bash/create-new-feature.sh --json "$ARGUMENTS" -Json -Number 5 -ShortName "user-auth" "Add user authentication"`
**IMPORTANT**:
- Check all three sources (remote branches, local branches, specs directories) to find the highest number
- Only match branches/directories with the exact short-name pattern
- If no existing branches/directories found with this short-name, start with number 1
- You must only ever run this script once per feature
- The JSON is provided in the terminal as output - always refer to it to get the actual content you're looking for
- The JSON output will contain BRANCH_NAME and SPEC_FILE paths
- For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot")
3. Load `.specify/templates/spec-template.md` to understand required sections.
4. **Generate UX Reference**:
a. Load `.specify/templates/ux-reference-template.md`.
b. **Design the User Experience**:
- **Imagine you are the user**: Visualize the interface and interaction.
- **Persona**: Define who is using this.
- **Happy Path**: Write the story of the perfect interaction.
- **Mockups**: Create concrete CLI text blocks or UI descriptions.
- **Errors**: Define how the system guides the user out of failure.
c. Write the `ux_reference.md` file in the feature directory.
d. **CRITICAL**: This UX Reference is now the source of truth for the "feel" of the feature. The technical spec MUST support this experience.
5. Follow this execution flow:
1. Parse user description from Input
If empty: ERROR "No feature description provided"
2. Extract key concepts from description
Identify: actors, actions, data, constraints
3. For unclear aspects:
- Make informed guesses based on context and industry standards
- Only mark with [NEEDS CLARIFICATION: specific question] if:
- The choice significantly impacts feature scope or user experience
- Multiple reasonable interpretations exist with different implications
- No reasonable default exists
- **LIMIT: Maximum 3 [NEEDS CLARIFICATION] markers total**
- Prioritize clarifications by impact: scope > security/privacy > user experience > technical details
4. Fill User Scenarios & Testing section
If no clear user flow: ERROR "Cannot determine user scenarios"
5. Generate Functional Requirements
Each requirement must be testable
Use reasonable defaults for unspecified details (document assumptions in Assumptions section)
6. Define Success Criteria
Create measurable, technology-agnostic outcomes
Include both quantitative metrics (time, performance, volume) and qualitative measures (user satisfaction, task completion)
Each criterion must be verifiable without implementation details
7. Identify Key Entities (if data involved)
8. Return: SUCCESS (spec ready for planning)
5. Write the specification to SPEC_FILE using the template structure, replacing placeholders with concrete details derived from the feature description (arguments) while preserving section order and headings.
6. **Specification Quality Validation**: After writing the initial spec, validate it against quality criteria:
a. **Create Spec Quality Checklist**: Generate a checklist file at `FEATURE_DIR/checklists/requirements.md` using the checklist template structure with these validation items:
```markdown
# Specification Quality Checklist: [FEATURE NAME]
**Purpose**: Validate specification completeness and quality before proceeding to planning
**Created**: [DATE]
**Feature**: [Link to spec.md]
## Content Quality
- [ ] No implementation details (languages, frameworks, APIs)
- [ ] Focused on user value and business needs
- [ ] Written for non-technical stakeholders
- [ ] All mandatory sections completed
## UX Consistency
- [ ] Functional requirements fully support the 'Happy Path' in ux_reference.md
- [ ] Error handling requirements match the 'Error Experience' in ux_reference.md
- [ ] No requirements contradict the defined User Persona or Context
## Requirement Completeness
- [ ] No [NEEDS CLARIFICATION] markers remain
- [ ] Requirements are testable and unambiguous
- [ ] Success criteria are measurable
- [ ] Success criteria are technology-agnostic (no implementation details)
- [ ] All acceptance scenarios are defined
- [ ] Edge cases are identified
- [ ] Scope is clearly bounded
- [ ] Dependencies and assumptions identified
## Feature Readiness
- [ ] All functional requirements have clear acceptance criteria
- [ ] User scenarios cover primary flows
- [ ] Feature meets measurable outcomes defined in Success Criteria
- [ ] No implementation details leak into specification
## Notes
- Items marked incomplete require spec updates before `/speckit.clarify` or `/speckit.plan`
```
b. **Run Validation Check**: Review the spec against each checklist item:
- For each item, determine if it passes or fails
- Document specific issues found (quote relevant spec sections)
c. **Handle Validation Results**:
- **If all items pass**: Mark checklist complete and proceed to step 6
- **If items fail (excluding [NEEDS CLARIFICATION])**:
1. List the failing items and specific issues
2. Update the spec to address each issue
3. Re-run validation until all items pass (max 3 iterations)
4. If still failing after 3 iterations, document remaining issues in checklist notes and warn user
- **If [NEEDS CLARIFICATION] markers remain**:
1. Extract all [NEEDS CLARIFICATION: ...] markers from the spec
2. **LIMIT CHECK**: If more than 3 markers exist, keep only the 3 most critical (by scope/security/UX impact) and make informed guesses for the rest
3. For each clarification needed (max 3), present options to user in this format:
```markdown
## Question [N]: [Topic]
**Context**: [Quote relevant spec section]
**What we need to know**: [Specific question from NEEDS CLARIFICATION marker]
**Suggested Answers**:
| Option | Answer | Implications |
|--------|--------|--------------|
| A | [First suggested answer] | [What this means for the feature] |
| B | [Second suggested answer] | [What this means for the feature] |
| C | [Third suggested answer] | [What this means for the feature] |
| Custom | Provide your own answer | [Explain how to provide custom input] |
**Your choice**: _[Wait for user response]_
```
4. **CRITICAL - Table Formatting**: Ensure markdown tables are properly formatted:
- Use consistent spacing with pipes aligned
- Each cell should have spaces around content: `| Content |` not `|Content|`
- Header separator must have at least 3 dashes: `|--------|`
- Test that the table renders correctly in markdown preview
5. Number questions sequentially (Q1, Q2, Q3 - max 3 total)
6. Present all questions together before waiting for responses
7. Wait for user to respond with their choices for all questions (e.g., "Q1: A, Q2: Custom - [details], Q3: B")
8. Update the spec by replacing each [NEEDS CLARIFICATION] marker with the user's selected or provided answer
9. Re-run validation after all clarifications are resolved
d. **Update Checklist**: After each validation iteration, update the checklist file with current pass/fail status
7. Report completion with branch name, spec file path, ux_reference file path, checklist results, and readiness for the next phase (`/speckit.clarify` or `/speckit.plan`).
**NOTE:** The script creates and checks out the new branch and initializes the spec file before writing.
## General Guidelines
## Quick Guidelines
- Focus on **WHAT** users need and **WHY**.
- Avoid HOW to implement (no tech stack, APIs, code structure).
- Written for business stakeholders, not developers.
- DO NOT create any checklists that are embedded in the spec. That will be a separate command.
### Section Requirements
- **Mandatory sections**: Must be completed for every feature
- **Optional sections**: Include only when relevant to the feature
- When a section doesn't apply, remove it entirely (don't leave as "N/A")
### For AI Generation
When creating this spec from a user prompt:
1. **Make informed guesses**: Use context, industry standards, and common patterns to fill gaps
2. **Document assumptions**: Record reasonable defaults in the Assumptions section
3. **Limit clarifications**: Maximum 3 [NEEDS CLARIFICATION] markers - use only for critical decisions that:
- Significantly impact feature scope or user experience
- Have multiple reasonable interpretations with different implications
- Lack any reasonable default
4. **Prioritize clarifications**: scope > security/privacy > user experience > technical details
5. **Think like a tester**: Every vague requirement should fail the "testable and unambiguous" checklist item
6. **Common areas needing clarification** (only if no reasonable default exists):
- Feature scope and boundaries (include/exclude specific use cases)
- User types and permissions (if multiple conflicting interpretations possible)
- Security/compliance requirements (when legally/financially significant)
**Examples of reasonable defaults** (don't ask about these):
- Data retention: Industry-standard practices for the domain
- Performance targets: Standard web/mobile app expectations unless specified
- Error handling: User-friendly messages with appropriate fallbacks
- Authentication method: Standard session-based or OAuth2 for web apps
- Integration patterns: RESTful APIs unless specified otherwise
### Success Criteria Guidelines
Success criteria must be:
1. **Measurable**: Include specific metrics (time, percentage, count, rate)
2. **Technology-agnostic**: No mention of frameworks, languages, databases, or tools
3. **User-focused**: Describe outcomes from user/business perspective, not system internals
4. **Verifiable**: Can be tested/validated without knowing implementation details
**Good examples**:
- "Users can complete checkout in under 3 minutes"
- "System supports 10,000 concurrent users"
- "95% of searches return results in under 1 second"
- "Task completion rate improves by 40%"
**Bad examples** (implementation-focused):
- "API response time is under 200ms" (too technical, use "Users see results instantly")
- "Database can handle 1000 TPS" (implementation detail, use user-facing metric)
- "React components render efficiently" (framework-specific)
- "Redis cache hit rate above 80%" (technology-specific)

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---
description: Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.
handoffs:
- label: Analyze For Consistency
agent: speckit.analyze
prompt: Run a project analysis for consistency
send: true
- label: Implement Project
agent: speckit.implement
prompt: Start the implementation in phases
send: true
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. **Setup**: Run `.specify/scripts/bash/check-prerequisites.sh --json` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Load design documents**: Read from FEATURE_DIR:
- **Required**: `plan.md` (tech stack, libraries, structure), `spec.md` (user stories with priorities), `ux_reference.md` (experience source of truth)
- **Optional**: `data-model.md` (entities), `contracts/` (API endpoints), `research.md` (decisions), `quickstart.md` (test scenarios)
- **Required when present in plan output**: ADR artifacts such as `docs/architecture.md` or feature-local architecture decision files containing `[DEF:id:ADR]` nodes
- Note: Not all projects have all documents. Generate tasks based on what's available.
3. **Execute task generation workflow**:
- Load `plan.md` and extract tech stack, libraries, project structure
- Load `spec.md` and extract user stories with their priorities (P1, P2, P3, etc.)
- Load ADR nodes and build a decision-memory inventory: `DecisionId`, `@RATIONALE`, `@REJECTED`, dependent modules
- If `data-model.md` exists: Extract entities and map to user stories
- If `contracts/` exists: Map endpoints to user stories
- If `research.md` exists: Extract decisions for setup tasks
- Generate tasks organized by user story (see Task Generation Rules below)
- Generate dependency graph showing user story completion order
- Create parallel execution examples per user story
- Validate task completeness (each user story has all needed tasks, independently testable)
- Validate guardrail continuity: no task may realize an ADR path named in `@REJECTED`
4. **Generate `tasks.md`**: Use `.specify/templates/tasks-template.md` as structure, fill with:
- Correct feature name from `plan.md`
- Phase 1: Setup tasks (project initialization)
- Phase 2: Foundational tasks (blocking prerequisites for all user stories)
- Phase 3+: One phase per user story (in priority order from `spec.md`)
- Each phase includes: story goal, independent test criteria, tests (if requested), implementation tasks
- Final Phase: Polish & cross-cutting concerns
- All tasks must follow the strict checklist format (see Task Generation Rules below)
- Clear file paths for each task
- Dependencies section showing story completion order
- Parallel execution examples per story
- Implementation strategy section (MVP first, incremental delivery)
- Decision-memory notes for guarded tasks when ADRs or known traps apply
5. **Report**: Output path to generated `tasks.md` and summary:
- Total task count
- Task count per user story
- Parallel opportunities identified
- Independent test criteria for each story
- Suggested MVP scope (typically just User Story 1)
- Format validation: Confirm ALL tasks follow the checklist format (checkbox, ID, labels, file paths)
- ADR propagation summary: which ADRs were inherited into task guardrails and which paths were rejected
Context for task generation: $ARGUMENTS
The `tasks.md` should be immediately executable - each task must be specific enough that an LLM can complete it without additional context.
## Task Generation Rules
**CRITICAL**: Tasks MUST be organized by user story to enable independent implementation and testing.
**Tests are OPTIONAL**: Only generate test tasks if explicitly requested in the feature specification or if user requests TDD approach.
### UX & Semantic Preservation (CRITICAL)
- **Source of Truth**: `ux_reference.md` for UX, `.ai/standards/semantics.md` for code, and ADR artifacts for upstream technology decisions.
- **Violation Warning**: If any task violates UX, ADR guardrails, or GRACE standards, flag it immediately.
- **Verification Task (UX)**: Add a task at the end of each Story phase: `- [ ] Txxx [USx] Verify implementation matches ux_reference.md (Happy Path & Errors)`
- **Verification Task (Audit)**: Add a mandatory audit task at the end of each Story phase: `- [ ] Txxx [USx] Acceptance: Perform semantic audit & algorithm emulation by Tester`
- **Guardrail Rule**: If an ADR or contract says `@REJECTED`, task text must not schedule that path as implementation work.
### Checklist Format (REQUIRED)
Every task MUST strictly follow this format:
```text
- [ ] [TaskID] [P?] [Story?] Description with file path
```
**Format Components**:
1. **Checkbox**: ALWAYS start with `- [ ]` (markdown checkbox)
2. **Task ID**: Sequential number (T001, T002, T003...) in execution order
3. **[P] marker**: Include ONLY if task is parallelizable (different files, no dependencies on incomplete tasks)
4. **[Story] label**: REQUIRED for user story phase tasks only
- Format: [US1], [US2], [US3], etc. (maps to user stories from `spec.md`)
- Setup phase: NO story label
- Foundational phase: NO story label
- User Story phases: MUST have story label
- Polish phase: NO story label
5. **Description**: Clear action with exact file path
**Examples**:
- ✅ CORRECT: `- [ ] T001 Create project structure per implementation plan`
- ✅ CORRECT: `- [ ] T005 [P] Implement authentication middleware in src/middleware/auth.py`
- ✅ CORRECT: `- [ ] T012 [P] [US1] Create User model in src/models/user.py`
- ✅ CORRECT: `- [ ] T014 [US1] Implement UserService in src/services/user_service.py`
- ❌ WRONG: `- [ ] Create User model` (missing ID and Story label)
- ❌ WRONG: `T001 [US1] Create model` (missing checkbox)
- ❌ WRONG: `- [ ] [US1] Create User model` (missing Task ID)
- ❌ WRONG: `- [ ] T001 [US1] Create model` (missing file path)
### Task Organization
1. **From User Stories (`spec.md`)** - PRIMARY ORGANIZATION:
- Each user story (P1, P2, P3...) gets its own phase
- Map all related components to their story:
- Models needed for that story
- Services needed for that story
- Endpoints/UI needed for that story
- If tests requested: Tests specific to that story
- Mark story dependencies (most stories should be independent)
2. **From Contracts (CRITICAL TIER)**:
- Identify components marked as `@TIER: CRITICAL` in `contracts/modules.md`.
- For these components, **MUST** append the summary of `@PRE`, `@POST`, `@UX_STATE`, and test contracts (`@TEST_FIXTURE`, `@TEST_EDGE`) directly to the task description.
- Example: `- [ ] T005 [P] [US1] Implement Auth (CRITICAL: PRE: token exists, POST: returns User, TESTS: 2 edges) in src/auth.py`
- Map each contract/endpoint → to the user story it serves
- If tests requested: Each contract → contract test task [P] before implementation in that story's phase
3. **From ADRs and Decision Memory**:
- For each implementation task constrained by an ADR, append a concise guardrail summary drawn from `@RATIONALE` and `@REJECTED`.
- Example: `- [ ] T021 [US1] Implement payload parsing guardrails in src/api/input.py (RATIONALE: strict validation because frontend sends numeric strings; REJECTED: json.loads() without schema validation)`
- If a task would naturally branch into an ADR-rejected alternative, rewrite the task around the accepted path instead of leaving the choice ambiguous.
- If no safe executable path remains because ADR context is incomplete, stop and emit `[NEED_CONTEXT: target]`.
4. **From Data Model**:
- Map each entity to the user story(ies) that need it
- If entity serves multiple stories: Put in earliest story or Setup phase
- Relationships → service layer tasks in appropriate story phase
5. **From Setup/Infrastructure**:
- Shared infrastructure → Setup phase (Phase 1)
- Foundational/blocking tasks → Foundational phase (Phase 2)
- Story-specific setup → within that story's phase
### Phase Structure
- **Phase 1**: Setup (project initialization)
- **Phase 2**: Foundational (blocking prerequisites - MUST complete before user stories)
- **Phase 3+**: User Stories in priority order (P1, P2, P3...)
- Within each story: Tests (if requested) → Models → Services → Endpoints → Integration
- Each phase should be a complete, independently testable increment
- **Final Phase**: Polish & Cross-Cutting Concerns
### Decision-Memory Validation Gate
Before finalizing `tasks.md`, verify all of the following:
- Every repo-shaping ADR from planning is either represented in a setup/foundational task or inherited by a downstream story task.
- Every guarded task that could tempt an implementer into a known wrong branch carries preventive `@RATIONALE` / `@REJECTED` guidance in its text.
- No task instructs the implementer to realize an ADR path already named as rejected.
- At least one explicit audit/verification task exists for checking rejected-path regressions in code review or test stages.

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---
description: Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.
tools: ['github/github-mcp-server/issue_write']
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. Run `.specify/scripts/bash/check-prerequisites.sh --json --require-tasks --include-tasks` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
1. From the executed script, extract the path to **tasks**.
1. Get the Git remote by running:
```bash
git config --get remote.origin.url
```
> [!CAUTION]
> ONLY PROCEED TO NEXT STEPS IF THE REMOTE IS A GITHUB URL
1. For each task in the list, use the GitHub MCP server to create a new issue in the repository that is representative of the Git remote.
> [!CAUTION]
> UNDER NO CIRCUMSTANCES EVER CREATE ISSUES IN REPOSITORIES THAT DO NOT MATCH THE REMOTE URL

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---
description: Generate tests, manage test documentation, and ensure maximum code coverage
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Goal
Execute semantic audit and full testing cycle: verify contract compliance, verify decision-memory continuity, emulate logic, ensure maximum coverage, and maintain test quality.
## Operating Constraints
1. **NEVER delete existing tests** - Only update if they fail due to bugs in the test or implementation
2. **NEVER duplicate tests** - Check existing tests first before creating new ones
3. **Use TEST_FIXTURE fixtures** - For CRITICAL tier modules, read @TEST_FIXTURE from .ai/standards/semantics.md
4. **Co-location required** - Write tests in `__tests__` directories relative to the code being tested
5. **Decision-memory regression guard** - Tests and audits must not normalize silent reintroduction of any path documented in upstream `@REJECTED`
## Execution Steps
### 1. Analyze Context
Run `.specify/scripts/bash/check-prerequisites.sh --json --require-tasks --include-tasks` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS.
Determine:
- FEATURE_DIR - where the feature is located
- TASKS_FILE - path to `tasks.md`
- Which modules need testing based on task status
- Which ADRs or task guardrails define rejected paths for the touched scope
### 2. Load Relevant Artifacts
**From `tasks.md`:**
- Identify completed implementation tasks (not test tasks)
- Extract file paths that need tests
- Extract guardrail summaries and blocked paths
**From `.ai/standards/semantics.md`:**
- Read effective complexity expectations
- Read decision-memory rules for ADR, preventive guardrails, and reactive Micro-ADR
- For CRITICAL modules: Read `@TEST_` fixtures
**From ADR sources and touched code:**
- Read `[DEF:id:ADR]` nodes when present
- Read local `@RATIONALE` and `@REJECTED` in touched contracts
**From existing tests:**
- Scan `__tests__` directories for existing tests
- Identify test patterns and coverage gaps
### 3. Test Coverage Analysis
Create coverage matrix:
| Module | File | Has Tests | Complexity / Tier | TEST_FIXTURE Available | Rejected Path Guarded |
|--------|------|-----------|-------------------|------------------------|-----------------------|
| ... | ... | ... | ... | ... | ... |
### 4. Semantic Audit & Logic Emulation (CRITICAL)
Before writing tests, the Tester MUST:
1. **Run `axiom-core.audit_contracts_tool`**: Identify semantic violations.
2. **Run a protocol-shape review on touched files**:
- Reject non-canonical semantic markup, including docstring-only annotations such as `@PURPOSE`, `@PRE`, or `@INVARIANT` written inside class/function docstrings without canonical `[DEF]...[/DEF]` anchors and header metadata.
- Reject files whose effective complexity contract is under-specified relative to [`.ai/standards/semantics.md`](.ai/standards/semantics.md).
- Reject Python Complexity 4+ modules that omit meaningful `logger.reason()` / `logger.reflect()` checkpoints.
- Reject Python Complexity 5 modules that omit `belief_scope(...)`, `@DATA_CONTRACT`, or `@INVARIANT`.
- Treat broken or missing closing anchors as blocking violations.
- Reject retained workaround code if the local contract lacks `@RATIONALE` / `@REJECTED`.
- Reject code that silently re-enables a path declared in upstream ADR or local guardrails as rejected.
3. **Emulate Algorithm**: Step through the code implementation in mind.
- Verify it adheres to the `@PURPOSE` and `@INVARIANT`.
- Verify `@PRE` and `@POST` conditions are correctly handled.
- Verify the implementation follows accepted-path rationale rather than drifting into a blocked path.
4. **Validation Verdict**:
- If audit fails: Emit `[AUDIT_FAIL: semantic_noncompliance]` with concrete file-path reasons and notify Orchestrator.
- Example blocking case: [`backend/src/services/dataset_review/repositories/session_repository.py`](backend/src/services/dataset_review/repositories/session_repository.py) contains a module anchor, but its nested repository class/method semantics are expressed as loose docstrings instead of canonical anchored contracts; this MUST be rejected until remediated or explicitly waived.
- If audit passes: Proceed to writing/verifying tests.
### 5. Write Tests (TDD Approach)
For each module requiring tests:
1. **Check existing tests**: Scan `__tests__/` for duplicates.
2. **Read TEST_FIXTURE**: If CRITICAL tier, read `@TEST_FIXTURE` from semantics header.
3. **Do not normalize broken semantics through tests**:
- The Tester must not write tests that silently accept malformed semantic protocol usage.
- If implementation is semantically invalid, stop and reject instead of adapting tests around the invalid structure.
4. **Write test**: Follow co-location strategy.
- Python: `src/module/__tests__/test_module.py`
- Svelte: `src/lib/components/__tests__/test_component.test.js`
5. **Use mocks**: Use `unittest.mock.MagicMock` for external dependencies
6. **Add rejected-path regression coverage when relevant**:
- If ADR or local contract names a blocked path in `@REJECTED`, add or verify at least one test or explicit audit check that would fail if that forbidden path were silently restored.
### 4a. UX Contract Testing (Frontend Components)
For Svelte components with `@UX_STATE`, `@UX_FEEDBACK`, `@UX_RECOVERY` tags:
1. **Parse UX tags**: Read component file and extract all `@UX_*` annotations
2. **Generate UX tests**: Create tests for each UX state transition
```javascript
// Example: Testing @UX_STATE: Idle -> Expanded
it('should transition from Idle to Expanded on toggle click', async () => {
render(Sidebar);
const toggleBtn = screen.getByRole('button', { name: /toggle/i });
await fireEvent.click(toggleBtn);
expect(screen.getByTestId('sidebar')).toHaveClass('expanded');
});
```
3. **Test `@UX_FEEDBACK`**: Verify visual feedback (toast, shake, color changes)
4. **Test `@UX_RECOVERY`**: Verify error recovery mechanisms (retry, clear input)
5. **Use `@UX_TEST` fixtures**: If component has `@UX_TEST` tags, use them as test specifications
6. **Verify decision memory**: If the UI contract declares `@REJECTED`, ensure browser-visible behavior does not regress into the rejected path.
**UX Test Template:**
```javascript
// [DEF:ComponentUXTests:Module]
// @C: 3
// @RELATION: VERIFIES -> ../Component.svelte
// @PURPOSE: Test UX states and transitions
describe('Component UX States', () => {
// @UX_STATE: Idle -> {action: click, expected: Active}
it('should transition Idle -> Active on click', async () => { ... });
// @UX_FEEDBACK: Toast on success
it('should show toast on successful action', async () => { ... });
// @UX_RECOVERY: Retry on error
it('should allow retry on error', async () => { ... });
});
// [/DEF:__tests__/test_Component:Module]
```
### 5. Test Documentation
Create/update documentation in `specs/<feature>/tests/`:
```
tests/
├── README.md # Test strategy and overview
├── coverage.md # Coverage matrix and reports
└── reports/
└── YYYY-MM-DD-report.md
```
Include decision-memory coverage notes when ADR or rejected-path regressions were checked.
### 6. Execute Tests
Run tests and report results:
**Backend:**
```bash
cd backend && .venv/bin/python3 -m pytest -v
```
**Frontend:**
```bash
cd frontend && npm run test
```
### 7. Update Tasks
Mark test tasks as completed in `tasks.md` with:
- Test file path
- Coverage achieved
- Any issues found
- Whether rejected-path regression checks passed or remain manual audit items
## Output
Generate test execution report:
```markdown
# Test Report: [FEATURE]
**Date**: [YYYY-MM-DD]
**Executed by**: Tester Agent
## Coverage Summary
| Module | Tests | Coverage % |
|--------|-------|------------|
| ... | ... | ... |
## Test Results
- Total: [X]
- Passed: [X]
- Failed: [X]
- Skipped: [X]
## Semantic Audit Verdict
- Verdict: PASS | FAIL
- Blocking Violations:
- [file path] -> [reason]
- Decision Memory:
- ADRs checked: [...]
- Rejected-path regressions: PASS | FAIL
- Missing `@RATIONALE` / `@REJECTED`: [...]
- Notes:
- Reject docstring-only semantic pseudo-markup
- Reject complexity/contract mismatches
- Reject missing belief-state instrumentation for Python Complexity 4/5
- Reject silent resurrection of rejected paths
## Issues Found
| Test | Error | Resolution |
|------|-------|------------|
| ... | ... | ... |
## Next Steps
- [ ] Fix failed tests
- [ ] Fix blocking semantic violations before acceptance
- [ ] Fix decision-memory drift or rejected-path regressions
- [ ] Add more coverage for [module]
- [ ] Review TEST_FIXTURE fixtures
```
## Context for Testing
$ARGUMENTS