--- 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