/plan

This skill is self-contained — follow the steps below instead of delegating to external planning skills (superpowers, etc.).

Research the codebase and create a spec + phased implementation plan. Zero interactive questions — explores the code instead.

When to use

Creates a track for any feature, bug fix, or refactor with a concrete, file-level implementation plan. Works with or without /setup.

MCP Tools (use if available)

• session_search(query) — find similar past work in Claude Code chat history
• project_code_search(query, project) — find reusable code across projects
• codegraph_query(query) — check dependencies of affected files
• codegraph_explain(project) — architecture overview: stack, languages, directory layers, key patterns, top dependencies, hub files
• kb_search(query) — search knowledge base for relevant methodology

If MCP tools are not available, fall back to Glob + Grep + Read.

Steps

1. Parse task description from $ARGUMENTS.
2. If empty, ask via AskUserQuestion: "What feature, bug, or refactor do you want to plan?"

3. This is the ONE question maximum.

4. Detect context — determine where plan files should be stored:

Project context (normal project with code): - Detected by: package.json, pyproject.toml, Cargo.toml, *.xcodeproj, or build.gradle.kts exists in working directory - Plan path: docs/plan/{trackId}/

Knowledge base context (documentation-centric project): - Detected by: NO package manifest found, BUT directories like docs/, notes/, or structured numbered directories exist - Plan path: docs/plan/{shortname}/ - Note: the shortname is derived from the task (kebab-case, no date suffix for the directory)

Set $PLAN_ROOT based on detected context. All subsequent file paths use $PLAN_ROOT.

1. Load project context (parallel reads):
2. CLAUDE.md — architecture, constraints, Do/Don't
3. docs/prd.md — what the product does (if exists)
4. docs/workflow.md — TDD policy, commit strategy (if exists)

5. package.json or pyproject.toml — stack, versions, deps

6. Auto-classify track type from keywords in task description:

7. Contains "fix", "bug", "broken", "error", "crash" → bug
8. Contains "refactor", "cleanup", "reorganize", "migrate" → refactor
9. Contains "update", "upgrade", "bump" → chore

10. Default → feature

11. Research phase — explore the codebase to understand what needs to change:

a. Get architecture overview (if MCP available — do this FIRST): codegraph_explain(project="{project name from CLAUDE.md or directory name}") Gives you: stack, languages, directory layers, key patterns, top dependencies, hub files.

b. Find relevant files — Glob + Grep for patterns related to the task: - Search for keywords from the task description - Look at directory structure to understand architecture - Identify files that will need modification

c. Precedent retrieval (context graph pattern — search past solutions BEFORE planning): - Search past sessions (if MCP available): session_search(query="{task description keywords}") Look for: how similar tasks were solved, what went wrong, what patterns worked. - Search KB for relevant methodology: kb_search(query="{task type}: {keywords}") Check for: harness patterns, architectural constraints, quality scores.

d. Search code across projects (if MCP available): project_code_search(query="{relevant pattern}")

e. Check dependencies of affected files (if MCP available): codegraph_query(query="MATCH (f:File {path: '{file}'})-[:IMPORTS]->(dep) RETURN dep.path")

f. Read existing tests in the affected area — understand testing patterns used.

g. Read CLAUDE.md architecture constraints — understand boundaries and conventions. - Check for harness section: module boundaries, data validation rules, lint configs. - Read docs/ARCHITECTURE.md and docs/QUALITY_SCORE.md if they exist.

h. Detect deploy infrastructure — search for deploy scripts/configs to include deploy phase in plan: bash find . -maxdepth 3 ( -name 'deploy.sh' -o -name 'Dockerfile' -o -name 'docker-compose.yml' -o -name 'fly.toml' -o -name 'wrangler.toml' ) -type f 2>/dev/null If found, read them to understand deploy targets. Include a deploy phase in the plan with concrete commands.

1. Generate track ID:
2. Extract a short name (2-3 words, kebab-case) from task description.

3. Format: {shortname}_{YYYYMMDD} (e.g., user-auth_20260209).

4. Create track directory: bash mkdir -p $PLAN_ROOT

5. Project context: docs/plan/{trackId}/

6. KB context: docs/plan/{shortname}/

7. Generate $PLAN_ROOT/spec.md: Based on research findings, NOT generic questions. ```markdown # Specification: {Title}

Track ID: {trackId} Type: {Feature|Bug|Refactor|Chore} Created: {YYYY-MM-DD} Status: Draft

## Summary

## Acceptance Criteria - [ ] {concrete, testable criterion} - [ ] {concrete, testable criterion}

## Dependencies - {external deps, packages, other tracks}

## Out of Scope - {what this track does NOT cover}

## Technical Notes - {architecture decisions from research} - {relevant patterns found in codebase} - {reusable code from other projects} ```

1. Generate $PLAN_ROOT/plan.md: Concrete, file-level plan from research. Keep it tight: 2-4 phases, 5-15 tasks total.

Critical format rules (parsed by /build): - Phase headers: ## Phase N: Name - Tasks: - [ ] Task N.Y: Description (with period or detailed text) - Subtasks: indented - [ ] Subtask description - All tasks use [ ] (unchecked), [~] (in progress), [x] (done)

```markdown # Implementation Plan: {Title}

Track ID: {trackId} Spec: spec.md Created: {YYYY-MM-DD} Status: [ ] Not Started

## Overview

## Phase 1: {Name}

### Tasks - [ ] Task 1.1: {description with concrete file paths} - [ ] Task 1.2: {description}

### Verification - [ ] {what to check after this phase}

## Phase 2: {Name} ### Tasks - [ ] Task 2.1: {description} - [ ] Task 2.2: {description}

### Verification - [ ] {verification steps}

{2-4 phases total}

## Phase {N-1}: Deploy (if deploy infrastructure exists) Include this phase ONLY if the project has deploy scripts/configs (deploy.sh, Dockerfile, docker-compose.yml, fly.toml, wrangler.toml, vercel.json). Skip if no deploy infra found.

### Tasks - [ ] Task {N-1}.1: {concrete deploy step — e.g. "Run python/deploy.sh to push Docker image to VPS", "wrangler deploy", etc.} - [ ] Task {N-1}.2: Verify deployment — health check, logs, HTTP status

### Verification - [ ] Service is live and healthy - [ ] No runtime errors in production logs

## Phase {N}: Docs & Cleanup ### Tasks - [ ] Task {N}.1: Update CLAUDE.md with any new commands, architecture changes, or key files - [ ] Task {N}.2: Update README.md if public API or setup steps changed - [ ] Task {N}.3: Remove dead code — unused imports, orphaned files, stale exports

### Verification - [ ] CLAUDE.md reflects current project state - [ ] Linter clean, tests pass

## Final Verification - [ ] All acceptance criteria from spec met - [ ] Tests pass - [ ] Linter clean - [ ] Build succeeds - [ ] Documentation up to date

---

Generated by /plan. Tasks marked [~] in progress and [x] complete by /build. ```

Plan quality rules: - Every task mentions specific file paths (from research). - Tasks are atomic — one commit each. - Phases are independently verifiable. - Total: 5-15 tasks (not 70). - Last phase is always "Docs & Cleanup". - Harness-aware: if the task introduces new patterns, include a task to update lint rules or CLAUDE.md constraints. If it touches module boundaries, include verification of dependency direction. Think: "what harness change prevents future agents from breaking this?"

1. Create progress task list for pipeline visibility:

After writing plan.md, create TaskCreate entries so progress is trackable: - One task per phase: "Phase 1: {name}" with task list as description. - This gives the user and pipeline real-time visibility into what's planned. - /build will update these tasks as it works through them.

If superpowers:writing-plans skill is available, follow its granularity format: bite-sized tasks (2-5 minutes each), complete code in task descriptions, exact file paths, verification steps per task. This enhances the built-in format above.

1. Show plan for approval via AskUserQuestion: Present the spec summary + plan overview. Options:
2. "Approve and start" — ready for /build
3. "Edit plan" — user wants to modify before implementing
4. "Cancel" — discard the track

If "Edit plan": tell user to edit $PLAN_ROOT/plan.md manually, then run /build.

Output

Track created: {trackId}

  Type:   {Feature|Bug|Refactor|Chore}
  Phases: {N}
  Tasks:  {N}
  Spec:   $PLAN_ROOT/spec.md
  Plan:   $PLAN_ROOT/plan.md

Research findings:
  - {key finding 1}
  - {key finding 2}
  - {reusable code found, if any}

Next: /build {trackId}

Rationalizations Catalog

These thoughts mean STOP — you're skipping research:

Thought	Reality
"I know this codebase"	You know what you've seen. Search for what you haven't.
"The plan is obvious"	Obvious plans miss edge cases. Research first.
"Let me just start coding"	10 minutes of research prevents 2 hours of rework.
"This is a small feature"	Small features touch many files. Map the blast radius.
"I'll figure it out as I go"	That's not a plan. Write the file paths first.
"70 tasks should cover it"	5-15 tasks. If you need more, split into tracks.

Compatibility Notes

• Plan format must match what /build parses: ## Phase N:, - [ ] Task N.Y:.
• /build reads docs/workflow.md for TDD policy and commit strategy (if exists).
• If docs/workflow.md missing, /build uses sensible defaults (moderate TDD, conventional commits).

Common Issues

Plan has too many tasks

Cause: Feature scope too broad or tasks not atomic enough. Fix: Target 5-15 tasks across 2-4 phases. Split large features into multiple tracks.

Context detection wrong (project vs KB)

Cause: Directory has both code manifests and KB-style directories. Fix: Project context takes priority if package.json/pyproject.toml exists.

Research phase finds no relevant code

Cause: New project with minimal codebase or MCP tools unavailable. Fix: Skill falls back to Glob + Grep. For new projects, the plan will rely more on CLAUDE.md architecture and stack conventions.