writing-plans
Skill24 starsChanged 25 days agoMITView on GitHub
Create a detailed, phased implementation plan from an approved spec. Use after brainstorming produces an approved spec. Produces a plan file that executing-plans or subagent-driven-development can consume.
187 other projects use a version of this.
Adopted by
Most recently taken up by
- DemonDamon/AgenticXtheir own version, first seen Nov 9, 2026
- roundpilot/superpowers-antigravitytheir own version, first seen Nov 8, 2026
- REPOZY/superpowers-optimizedtheir own version, first seen Nov 8, 2026
- lingyired/status-triotheir own version, first seen Nov 8, 2026
- ashleysbrain/skillstheir own version, first seen Nov 8, 2026
- ryanportfolio/winuse-mcptheir own version, first seen Nov 8, 2026
Used with
Projects with it also use chinese-code-review, chinese-commit-conventions and 10 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.
Leodorareluctant259Skillchinese-code-review
中文代码审查规范——在保持专业严谨的同时,用符合国内团队文化的方式给出有效反馈
Also in 8 projects that use this
Leodorareluctant259Skillchinese-commit-conventions
中文 Git 提交规范 — 适配国内团队的 commit message 规范和 changelog 自动化
Also in 8 projects that use this
ryanportfolioSkilladdskill
Create, import, update, or install repo or personal skills: runtime ownership, resources, discovery checks.
Also in 6 projects that use this
ryanportfolioSkillapply-firmware
Bring current folder (plain folder, existing repo, old or partial firmware copy) up to full Harness Firmware in place. Mirror external repo → adopt-repo.
Also in 6 projects that use this
- +2 more from Leodorareluctant259
- +6 more from ryanportfolio
Other versions187 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 187
- obra/superpowers★ 314ksame name
- jnMetaCode/superpowers-zh★ 8.4ksame name
- openai/plugins★ 7.8ksame name
- farm-fe/farm★ 5.6ksame name
- microsoft/FluidFramework★ 4.9ksame name
- lingyired/status-trio★ 1.8ksame name
- revokslab/ShipFree★ 1.7ksame name
- GanyuanRan/Aegis★ 1.4ksame name
- pcvelz/superpowers★ 1.3ksame name
- math-inc/OpenGauss★ 1.3ksame name
177 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository22 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/rules/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- api-contract-firstSkill
- architecture-auditSkill
- brainstormingSkill
- data-migrationSkill
- dispatching-parallel-agentsSkill
- executing-plansSkill
- finishing-a-development-branchSkill
- five-whysSkill
- incident-responseSkill
- performance-auditSkill
- skill-duplication-auditSkill
- smart-initSkill
- subagent-driven-developmentSkill
- systematic-debuggingSkill
- test-driven-developmentSkill
- using-a-teamSkill
- using-git-worktreesSkill
- verification-before-completionSkill
- writing-skillsSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 0 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 169 edited versions we read keep these.
0
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
- Very specific: line 8
Create implementation plans from approved specs.
- Very specific: line 14
Read the approved spec in docs/specs/
“Common” is measured: kept by at least 6 in 10 of the 169 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.
Files
Writing Plans
Create implementation plans from approved specs. The output is consumed by
executing-plans or subagent-driven-development.
Process
Step 1: Read the Spec
- Read the approved spec in
docs/specs/ - Identify: requirements, architecture changes, success criteria
- Note any open questions before planning
Step 2: Break Down Into Phases
Each phase must be:
- Independently deliverable — it can be merged on its own
- Incrementally testable — tests can verify it at the end of the phase
- Scope-bounded — clear start and end
Phase structure:
- Phase 1: Minimum viable (smallest slice with value)
- Phase 2: Core experience (complete happy path)
- Phase 3: Edge cases (error handling, polish)
- Phase 4: Optimization (performance, monitoring) — if needed
Step 3: Write Each Step
Each step must include:
- File: exact path
- Action: specific change to make
- Why: rationale
- Dependencies: which steps must precede this
- Risk: Low / Medium / High
Step 4: Add Testing Strategy
For each phase, specify:
- Unit tests: which functions/components
- Integration tests: which flows
- E2E tests: which user journeys
Step 5: Write Plan File
Save to docs/plans/YYYY-MM-DD-<feature>.md
# Implementation Plan: [Feature Name]
## Overview
[2-3 sentences]
## Requirements
- [Requirement 1]
## Architecture Changes
- [file path]: [description]
## Implementation Steps
### Phase 1: [Name] — Minimum Viable
1. **[Step]** (File: path/to/file.ts)
- Action: ...
- Why: ...
- Dependencies: None
- Risk: Low
## Testing Strategy
- Unit: [files]
- Integration: [flows]
- E2E: [journeys]
## Success Criteria
- [ ] Criterion 1Step 6: Confirm Plan with Human
Present the plan and confirm before execution begins.
Quality Checks
- Every step has an exact file path
- Every step has a specific action
- Phases are independently mergeable
- Testing strategy covers all new code paths
- No step is larger than 50 lines of code
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
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.

