agentleFS
mhyllemhylle/claude-skills-collection/skills/create-plan/SKILL.md

create-plan

Skill20 starsChanged 35 days agoMITView on GitHub

Create detailed implementation plans through interactive research and iteration. This skill should be used when creating new implementation plans, designing feature specifications, planning technical work, or when the user asks to plan an implementation. Triggers on requests like "create a plan", "plan the implementation", "design how to implement", or when given a feature/task that needs structured planning before implementation.

39 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use codebase-migrate, support-ticket-triage and 9 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • ComposioHQSkill

    codebase-migrate

    Run large codebase migrations and multi-file refactors. Uses the Composio CLI to coordinate issue tracking, batched PRs, and CI verification while the agent executes the transforms locally across hundreds of files.

    Also in 5 projects that use this

  • ComposioHQSkill

    support-ticket-triage

    Triage customer support tickets/emails/chats into categories, priority, and next action; draft responses and create reproducible steps; use for Zendesk/Intercom/Help Scout exports or pasted threads.

    Also in 5 projects that use this

  • hebertzhuSkill

    develop-web-game

    Use when building or iterating on a web game and you need a tight implement-test-observe loop; prefer the bundled Playwright client, inspect screenshots and text state, and validate every meaningful change before moving on.

    Also in 3 projects that use this

  • petestewartSkill

    datadog-logs

    Query Datadog logs via the Logs Search API v2. Use when the user asks to "check the logs", "search logs", "find errors in Datadog", "look up logs for", "show me production logs", "check for errors", "search Datadog", or any request involving log search, error investigation, or production debugging that requires Datadog log data.

    Also in 3 projects that use this

  • +7 more from ComposioHQ

The file

Show its rules and text

We split this skill into the rules it gives an agent

28 rules. 0 are common, 26 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 37 edited versions we read keep these.

  • 26

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Create detailed, well-researched implementation plans through interactive collaboration and thorough codebase investigation.

    line 39
  2. Distinctive:

    Read all identified files completely: - no partial reads or summaries.

    line 83
  3. Distinctive:

    Before any design work, present findings:

    line 87
  4. Distinctive:

    Ask only questions that code investigation couldn't answer

    line 95
  5. Distinctive:

    Avoid questions answerable by reading more code

    line 97
  6. Distinctive:

    Wait for user response before proceeding.

    line 99
  7. Distinctive:

    Critical: Do not accept user corrections at face value.

    line 103
  8. Distinctive:

    When the user provides corrections or additional context:

    line 105
  9. Distinctive:

    Verify claims through code investigation

    line 106
  10. Distinctive:

    If conflicts exist, present findings and discuss before proceeding.

    line 110
  11. Distinctive:

    Wait for user feedback on approach before detailing phases.

    line 132
  12. Distinctive:

    Before writing the detailed plan, validate phase sizing and present the structure.

    line 178
  13. Distinctive:

    Write the implementation plan to the designated location:

    line 217
  14. Distinctive:

    After writing the plan file, create Tasks for progress tracking:

    line 287
  15. Distinctive:

    Create a Task for each phase:

    line 293
  16. Distinctive:

    Add task list ID to plan metadata (top of file):

    line 308
  17. Distinctive:

    Every phase in the plan MUST include:

    line 355
  18. Distinctive:

    Specific test scenarios: - Not just "write tests" but what scenarios to cover

    line 359
  19. Distinctive:

    Read entire files, not partial content

    line 408
  20. Distinctive:

    Verify facts through code investigation

    line 409
  21. Distinctive:

    Follow import chains to understand dependencies

    line 410
  22. Distinctive:

    Start command executes without error

    line 434
  23. Distinctive:

    No runtime exceptions or crashes

    line 435
  24. Very specific:

    Test suites pass (npm test, pytest, go test)

    line 440
  25. Distinctive:

    If planning encounters ambiguity:

    line 450
  26. Distinctive:

    Stop and research further

    line 451
  27. Distinctive:

    Before finalizing any plan:

    line 459
  28. Very specific:

    Before writing exit conditions, detect the project type and use appropriate commands.

    line 496

“Common” is measured: kept by at least 6 in 10 of the 37 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Create Plan

<!-- contents: generated by tests/skill_structure.py --write; edit headings, not this block -->

Contents

  • When to Use This Skill
  • Initial Input Handling
  • Planning Workflow
    • Phase 1: Research
    • Phase 2: Present Understanding
    • Phase 3: Research User Corrections
    • Phase 4: Design Options
    • Phase 4b: Document Decision (ADR)
    • Phase 5: Phase Structure Review
    • Phase 6: Write the Plan
    • Phase 7: Bootstrap Tasks
  • Multi-Session Support
  • Critical Guidelines
    • Verification-First Planning
    • Phase Granularity
    • Be Thorough
    • Be Interactive
    • Be Skeptical
    • Exit Conditions Are Blocking Gates
    • No Unresolved Questions
  • Quality Checklist
  • Progress Tracking
  • Project Type Detection

Reference files (open one when a step points to it):

  • references/exit-conditions.md: Exit Condition Templates by Project Type
<!-- /contents -->

Create detailed, well-researched implementation plans through interactive collaboration and thorough codebase investigation.

When to Use This Skill

  • Planning new features or functionality
  • Designing technical implementations before coding
  • Creating phased development roadmaps
  • Structuring complex refactoring work
  • Any task requiring upfront planning and design

Initial Input Handling

Parse the user's request to identify:

  1. Task description - What needs to be implemented
  2. Context files - Relevant existing code or documentation
  3. Constraints - Timeline, technology, or scope limitations
ScenarioAction
Parameters providedRead all referenced files completely, then proceed to Research
Missing task descriptionAsk: "What feature or functionality should I plan?"
No context providedAsk: "Are there existing files or documentation I should review?"

Planning Workflow

Phase 1: Research

Critical: Thoroughly investigate the codebase before planning.

Spawn parallel sub-tasks using specialized agents:

Research Tasks:
- codebase-locator: Find all files related to the feature area
- codebase-analyzer: Understand existing patterns and architecture
- Explore: Investigate integration points and dependencies

For each research task, provide:

  • Specific directories to examine
  • Exact patterns or code to find
  • Required output: file:line references

Read all identified files completely - no partial reads or summaries.

Phase 2: Present Understanding

Before any design work, present findings:

  1. Codebase Analysis
    • Relevant existing code with file:line references
    • Current patterns and conventions discovered
    • Integration points and dependencies
  2. Clarifying Questions
    • Ask only questions that code investigation couldn't answer
    • Focus on business logic, user requirements, edge cases
    • Avoid questions answerable by reading more code

Wait for user response before proceeding.

Phase 3: Research User Corrections

Critical: Do not accept user corrections at face value.

When the user provides corrections or additional context:

  1. Verify claims through code investigation
  2. Cross-reference with discovered patterns
  3. Resolve any conflicts between user input and codebase reality

If conflicts exist, present findings and discuss before proceeding.

Phase 4: Design Options

Present design approaches with trade-offs:

Option A: [Approach Name]
- Description: [How it works]
- Pros: [Benefits]
- Cons: [Drawbacks]
- Fits pattern: [Reference to existing codebase patterns]

Option B: [Alternative Approach]
- Description: [How it works]
- Pros: [Benefits]
- Cons: [Drawbacks]
- Fits pattern: [Reference to existing codebase patterns]

Recommendation: [Preferred option with rationale]

Wait for user feedback on approach before detailing phases.

Phase 4b: Document Decision (ADR)

Before creating a new ADR, check for existing related decisions:

# Tiered ADR reading (context conservation)
1. Read("docs/decisions/INDEX.md")           # Scan all ADRs
2. Read("docs/decisions/ADR-NNNN.md", limit=10)  # Quick Reference only
3. Read full ADR only if directly relevant

After user approves a design option, invoke the ADR skill to document the decision:

Skill(skill="adr"): Document the design decision just made.

Context: [Why this decision was needed - from research phase]
Options Considered: [List options from Phase 4]
Decision: [The chosen option]
Rationale: [Why this option was selected]
Consequences: [Expected impacts]

The ADR will be created at docs/decisions/ADR-NNNN-title.md and INDEX.md will be updated.

Update the plan to reference the ADR in the Design Decision section:

## Design Decision

[Brief description of chosen approach]

See [ADR-NNNN](../decisions/ADR-NNNN-title.md) for full rationale and alternatives considered.

When to create ADRs during planning:

  • Choosing between architectural approaches
  • Selecting technologies or libraries
  • Establishing new patterns or conventions
  • Making trade-offs with significant implications
  • Decisions that future developers will question "why?"

Phase 5: Phase Structure Review

Before writing the detailed plan, validate phase sizing and present the structure.

Phase Sizing Guide

Plans fail during execution when phases are too large or vague. Each phase will be executed by an orchestrator that delegates to subagents — so every task in a phase needs to be concrete enough that an independent agent can implement it without guessing.

Bias toward smaller phases. 12 small well-defined phases are far better than 5 large ones. A phase that tries to do too much will overwhelm the implementing agent, cause it to lose focus, or force it to make assumptions about parts it hasn't reached yet. When in doubt, split. A complex feature might need 8-15 phases — that reflects the natural decomposition of the work, not a failure of planning.

A natural layered decomposition often emerges: foundation/setup → data model → core logic → API/interface → integration → polish/edge cases. Each layer is typically one phase.

Right-sized phase characteristics:

  • Has one concern — a single coherent unit of work
  • Touches a small number of files (1-5 is typical, occasionally more for cross-cutting changes)
  • Each task names a specific file and describes what to put in it (functions, classes, methods, endpoints)
  • Can be described in 2 sentences — if you need more, split it
  • Has a clear, testable outcome — you can verify it works without looking at later phases

Split signals — if any of these are true, the phase is too big:

  • It contains the word "and" connecting unrelated concerns (e.g., "implement auth and set up the database schema")
  • Two tasks within it could be developed and tested independently
  • It mixes infrastructure/config work with feature implementation

Present the Structure

Proposed Implementation Phases:

Phase 1: [Name] - [2-sentence description] ([N] files)
Phase 2: [Name] - [2-sentence description] ([N] files)
Phase 3: [Name] - [2-sentence description] ([N] files)
...

Does this structure make sense? Any phases to add/remove/reorder?

Get explicit approval before writing the full plan.

Phase 6: Write the Plan

Write the implementation plan to the designated location:

Default path: docs/plans/YYYY-MM-DD-description.md

Use this structure:

# Implementation Plan: [Feature Name]

## Overview
[2-3 sentence summary of what will be implemented]

## Context
[Background, motivation, relevant existing code references]

## Design Decision
[Chosen approach and rationale]

**ADR Reference**: [ADR-NNNN](../decisions/ADR-NNNN-title.md)

## Related ADRs
- [ADR-NNNN](../decisions/ADR-NNNN-title.md): [Brief description of relevance]

## Implementation Phases

### Phase 1: [Name]

**Objective**: [1-2 sentences — what this phase accomplishes and what it produces]

**Files touched**: [List every file this phase creates or modifies]

**Verification Approach**: [How will we verify this phase works? What tests, commands, or checks will confirm success?]

**Tasks** (tests first, then implementation):
- [ ] Create `[test-file-path]`: test [specific scenarios — name them]
- [ ] Create `[file-path]`: implement `ClassName` with `method1()`, `method2()` — [what each does, 5-10 words per method]
- [ ] Modify `[file-path]`: add [what — e.g., "import and register AuthModule"]
- [ ] Verify: [specific command]

**Exit Conditions**:

> Phase cannot proceed until ALL conditions pass.

Build Verification:
- [ ] `[build command]` succeeds
- [ ] `[lint command]` passes
- [ ] `[typecheck command]` passes (if applicable)

Runtime Verification:
- [ ] Application starts: `[start command]`
- [ ] No runtime errors in console
- [ ] [Service/endpoint] is accessible at [URL]

Functional Verification:
- [ ] `[test command]` passes
- [ ] [Specific test]: `[targeted test command]`
- [ ] [Manual check]: [Observable behavior to verify]

### Phase 2: [Name]
[Continue pattern...]

## Dependencies
[External dependencies, prerequisites, blockers]

## Risks and Mitigations
[Potential issues and how to handle them]

Phase 7: Bootstrap Tasks

After writing the plan file, create Tasks for progress tracking:

Process:

  1. Generate a task list ID from plan filename: plan-{filename-without-extension}
    • Example: 2026-01-24-user-auth.md → plan-2026-01-24-user-auth
  2. Create a Task for each phase:
    TaskCreate:
      subject: "Phase N: [Phase Name]"
      description: "[Phase objective] - Plan: [plan file path]"
      activeForm: "Implementing Phase N: [Name]"
  3. Set sequential dependencies:
    TaskUpdate:
      taskId: [phase-N]
      addBlockedBy: [phase-(N-1)]  # Each phase blocked by previous
  4. Add task list ID to plan metadata (top of file):
    ---
    task_list_id: plan-2026-01-24-user-auth
    ---

Completion Message:

Plan created: [path]
Tasks created: [count] phases with sequential dependencies
Task List ID: [task_list_id]

To work on this plan:
  Single session:  /implement-plan [path]
  Multi-session:   CLAUDE_CODE_TASK_LIST_ID=[task_list_id] claude

Use the same task_list_id across sessions to share progress.

Multi-Session Support

Tasks persist on the filesystem and can be shared across Claude Code sessions.

Starting a shared session:

CLAUDE_CODE_TASK_LIST_ID=plan-2026-01-24-user-auth claude

Benefits:

  • Multiple developers can work on the same plan
  • Progress syncs automatically via shared task list
  • Dependency tracking prevents conflicts (blocked tasks visible)
  • Resume from any session with the same task_list_id

Task States:

◻ #1 Phase 1: Setup
◻ #2 Phase 2: Core Logic › blocked by #1
◻ #3 Phase 3: Integration › blocked by #2
◻ #4 Phase 4: Testing › blocked by #3

Critical Guidelines

Verification-First Planning

Every phase in the plan MUST include:

  1. Verification Approach - A clear statement of how success will be measured
  2. Tests before implementation - Task lists must show test creation BEFORE implementation
  3. Specific test scenarios - Not just "write tests" but what scenarios to cover

Phase Granularity

Phases are executed by an orchestrator that delegates each task to an independent subagent. If a task is vague, the subagent has to guess — and it often guesses wrong. The key question for each task: could a developer who's never seen this codebase complete this task based solely on this description?

Bad — too vague, too large:

### Phase 1: Authentication

**Objective**: Add authentication to the application

**Tasks**:
- [ ] Write tests for auth
- [ ] Implement auth service
- [ ] Implement auth controller
- [ ] Add auth middleware
- [ ] Verify: `npm test` passes

Problems: "auth service" doing what exactly? How many methods? What library? "Add auth middleware" — where, protecting which routes? A subagent receiving "Implement auth service" will either ask clarifying questions (stalling the orchestrator) or make assumptions that conflict with later tasks.

Good — specific, delegatable:

### Phase 1: Password Hashing and Token Generation

**Objective**: Create the core auth utilities — password hashing via bcrypt and JWT token generation. No HTTP layer yet.

**Files touched**: `src/auth/auth.service.ts`, `src/auth/auth.service.spec.ts`, `src/auth/auth.module.ts`

**Verification Approach**: Unit tests verify bcrypt hashing round-trips correctly and JWT tokens contain expected claims (sub, iat, exp).

**Tasks** (tests first, then implementation):
- [ ] Create `src/auth/auth.service.spec.ts`: test `hashPassword()` produces valid bcrypt hash, `comparePassword()` matches correct password and rejects wrong password, `generateToken()` returns JWT with `sub` and `exp` claims
- [ ] Create `src/auth/auth.service.ts`: implement `AuthService` with `hashPassword(plain): Promise<string>`, `comparePassword(plain, hash): Promise<boolean>`, `generateToken(userId): string` — uses bcrypt (10 rounds) and jsonwebtoken
- [ ] Create `src/auth/auth.module.ts`: register `AuthService` as provider, export it
- [ ] Verify: `npm test -- auth.service` passes

### Phase 2: Login Endpoint

**Objective**: Add POST /auth/login endpoint that validates credentials and returns a JWT. Depends on AuthService from Phase 1.

**Files touched**: `src/auth/auth.controller.ts`, `src/auth/auth.controller.spec.ts`, `src/auth/auth.module.ts`
...

Notice: Phase 1 has one concern (crypto utilities), Phase 2 has one concern (HTTP endpoint). Each task names exact files, functions, and behaviors. A feature like auth might have 6-8 phases — that's a strength, not a weakness. Small phases are easier to implement, test, and debug.

Be Thorough

  • Read entire files, not partial content
  • Verify facts through code investigation
  • Follow import chains to understand dependencies

Be Interactive

  • Get buy-in at each step
  • Allow course corrections throughout
  • Present options rather than dictating

Be Skeptical

  • Research user claims before accepting
  • Cross-reference multiple sources
  • Challenge assumptions with evidence

Exit Conditions Are Blocking Gates

Exit conditions are mandatory gates that must pass before advancing to the next phase. They are not advisory - they are requirements.

Three Verification Categories (all must pass):

  1. Build Verification - Code compiles and passes static analysis:
    • Build commands (npm run build, cargo build, go build)
    • Linting (npm run lint, flake8, golangci-lint)
    • Type checking (npm run typecheck, mypy, tsc --noEmit)
  2. Runtime Verification - Application actually runs:
    • Start command executes without error
    • No runtime exceptions or crashes
    • Services/endpoints become accessible
    • Health checks pass
  3. Functional Verification - Correct behavior:
    • Test suites pass (npm test, pytest, go test)
    • Specific feature tests pass
    • Manual verification steps (for human-observable behaviors)

Never skip a category - each phase must have at least one check in each category.

No Unresolved Questions

Do NOT write plans with open questions.

If planning encounters ambiguity:

  1. Stop and research further
  2. Present options to the user
  3. Get resolution before continuing

A plan with "TBD" or "to be determined" sections is incomplete.

Quality Checklist

Before finalizing any plan:

  • All relevant code has been read completely
  • File:line references are accurate and specific
  • Design fits existing codebase patterns
  • Phases are incrementally implementable
  • Each phase has one concern and touches a small number of files
  • Each task names specific files and describes what goes in them (classes, methods, functions)
  • No task is so vague that a developer unfamiliar with the project would need to ask clarifying questions
  • Each phase has a Verification Approach section
  • Tasks list tests BEFORE implementation
  • Exit conditions cover all three verification categories
  • No unresolved questions or TBD sections
  • User has approved structure and approach
  • Tasks bootstrapped with dependencies set
  • task_list_id added to plan metadata

Progress Tracking

Progress is tracked via Task tools which persist across sessions. See ADR-0001.

Task Persistence:

  • Tasks persist on filesystem between sessions
  • Dependencies ensure correct execution order
  • Multiple sessions can share the same task list via CLAUDE_CODE_TASK_LIST_ID

Workflow:

create-plan → TaskCreate (all phases) → Outputs task_list_id
                    ↓
implement-plan → TaskUpdate(in_progress) → implement-phase → TaskUpdate(completed)
                    ↓
Resume (any session) → CLAUDE_CODE_TASK_LIST_ID=xxx claude → TaskList shows progress

Project Type Detection

Before writing exit conditions, detect the project type and use appropriate commands. Read references/exit-conditions.md for detection heuristics and per-language templates (Node.js, Python, Go, Rust, Java, etc.).

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.