Generate execution-ready implementation plans from research docs - planning ONLY, no fixing or verifying.

MITAuto-check passedAgent Workflows

Install Plan Phase

skills CLI
$ npx skills add alchemiststudiosDOTai/harness-engineering --skill plan-phase -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alchemiststudiosDOTai/harness-engineering plan-phase --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alchemiststudiosDOTai/harness-engineering.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/plan-phase .claude/skills/plan-phase && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
plan-phase
GitHub stars
105
Token cost
~1.8k tokens
SKILL.md length
420 words
Files
1
Skills in repo
8
Repo updated
First seen
Licence
MIT

At a glance

Generate execution-ready implementation plans from research docs - planning ONLY, no fixing or verifying.

  • Works in 4 steps: Read Research Doc → Verify Git Freshness → Generate Plan File → …
  • Tasks that involve Planning
  • SKILL.md covers Overview, North Star Rule, When to Use and What This Skill Does NOT Do, plus 9 more sections
  • Calls git

What it does

Plan Phase is an agent skill from alchemiststudiosDOTai/harness-engineering. Generate execution-ready implementation plans from research docs - planning ONLY, no fixing or verifying. North Star is whether a JR developer can execute the plan with zero additional context.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Planning. The repository describes itself as: harness-engineering discussion of shortcuts, automation, hacks and overall productivity with code agents like claude code, codex, and other harness. The licence is MIT.

When your agent uses it

  • Tasks that involve Planning

Example prompts

  • “/plan-phase”

Requirements

  • Pre-approved tools (allowed-tools): Read, Edit, Write, Bash(git:*), Bash(grep:*), Bash(sed:*), Bash(awk:*), Bash(jq:*), Bash(date:*), Bash(find:*)

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Read Research Doc
  2. Verify Git Freshness
  3. Generate Plan File
  4. Plan Structure

What it can do on your machine

Read from SKILL.md and the folder at commit 7a9fa15. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Edit
    • Write
    • Bash(git:*)
    • Bash(grep:*)
    • Bash(sed:*)
    • Bash(awk:*)
    • Bash(jq:*)
    • Bash(date:*)
    • Bash(find:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Plan Phase loads about 1.8k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 420 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from alchemiststudiosDOTai/harness-engineering at commit 7a9fa15, republished under its MIT licence (© alchemiststudiosDOTai). 420 words, ~1,801 tokens.

Download SKILL.mdSave it as .claude/skills/plan-phase/SKILL.md (or your agent's skills folder).
name
plan-phase
description
Generate execution-ready implementation plans from research docs - planning ONLY, no fixing or verifying. North Star is whether a JR developer can execute the plan with zero additional context.
allowed-tools
Read, Edit, Write, Bash(git:*), Bash(grep:*), Bash(sed:*), Bash(awk:*), Bash(jq:*), Bash(date:*), Bash(find:*)
writes-to
.artifacts/plan/
hard-guards
NO code modifications during planning, NO fixes or verification, Focus ONLY on generating clear executable plans, Every task must be unambiguous to a JR…

Plan Phase

Overview

Generate execution-ready, coding-only implementation plans from research documents. The goal is to produce plans that any JR developer can execute immediately with zero ambiguity.

North Star Rule

If a JR developer picked this up, could they start coding immediately?

If the answer is "no" or "they'd need to ask clarifying questions," the plan is incomplete.

When to Use

  • User asks to "create a plan from research"
  • User references a research doc in .artifacts/research/
  • User wants "implementation steps" from findings
  • User asks to "break down into tasks" a researched topic

What This Skill Does NOT Do

❌ DON'T✅ DO INSTEAD
Fix code issuesDocument them as tasks to fix
Verify implementationsPlan verification steps
Run testsPlan what tests to write
Deploy anythingPlan deployment as a task
Make code changesDocument exactly what changes to make

Planning Workflow

1. Read Research Doc
Read from: .artifacts/research/<topic>.md
Extract: scope, constraints, target files, unresolved questions, proposed solutions
2. Verify Git Freshness
bash
# Capture current state
git rev-parse HEAD          # Commit SHA
git status --short          # Working tree status
3. Generate Plan File

Save as: .artifacts/plan/YYYY-MM-DD_HH-MM-SS_<topic>.md

4. Plan Structure
markdown
---
title: "<topic> implementation plan"
link: "<topic>-plan"
type: implementation_plan
ontological_relations:
  - relates_to: [[<research-link>]]
tags: [plan, <topic>, coding]
uuid: "<uuid>"
created_at: "<ISO-8601 timestamp>"
parent_research: ".artifacts/research/<file>.md"
git_commit_at_plan: "<short_sha>"
---

## Goal

- ONE singular coding-focused outcome
- Explicitly state what is OUT of scope (ops, deploy, excessive testing)

## Scope & Assumptions

- IN scope: (technical items only)
- OUT of scope: (what we're NOT doing)
- Assumptions: (frameworks, environments, libraries)

## Deliverables

- Source code modules, functions, or APIs
- Documentation limited to developer-level notes (not user docs)

## Readiness

- Preconditions: repos, libs, data schemas, sample inputs
- What must exist before starting

## Milestones

- M1: Skeleton & architecture setup
- M2: Core logic & data flow
- M3: Feature completion & refinement
- M4: Basic test(s) & integration hooks

## Work Breakdown (Tasks)

For EACH task, specify:
- **Task ID**: T001, T002, etc.
- **Summary**: What to do (present tense, actionable)
- **Owner**: who does it
- **Estimate**: time/complexity
- **Dependencies**: other task IDs
- **Target milestone**: M1-M4
- **Acceptance test**: Exactly ONE test that proves it works
- **Files/modules touched**: List exact paths

## Risks & Mitigations

Keep technical:
- Library stability issues
- API version drift
- Schema mismatch risks
- Breaking changes in dependencies

## Test Strategy

At most ONE new test per task, only for validating main coding work.
Focus on proving correctness, not coverage.

## References

- Research doc sections
- Key code references (file:line format)

## Final Gate

- **Output summary**: plan path, milestone count, tasks ready
- **Next step**: proceed to execute-phase with the generated plan path

Task Writing Guidelines

✅ Good Task
T003: Add user authentication middleware
- Create src/middleware/auth.ts with verifyToken() function
- Import in src/app.ts and apply to /api/* routes
- Acceptance: curl /api/users returns 401 without header, 200 with valid token
- Files: src/middleware/auth.ts, src/app.ts
- Milestone: M2
❌ Bad Task
T003: Fix auth
- Handle the auth stuff properly
- Make sure it works
Rules for Tasks
  1. Present tense, actionable: "Add function X" not "Function X should be added"
  2. File paths explicit: No "find the right place to put it"
  3. One acceptance test per task: Single proof of correctness
  4. No hand-waving: "Implement caching" → "Add Redis caching to src/cache.ts with get/set methods"
  5. Depend on tasks, not people: "Depends on T001" not "Wait for backend team"

Git Freshness Check

Always capture and include:

bash
COMMIT_SHA=$(git rev-parse --short HEAD)
STATUS=$(git status --short)

If research doc mentions specific commits/branches and they've changed:

  • Mark affected tasks for re-verification
  • Note the discrepancy in plan frontmatter
Show full SKILL.md (163 more words)Show less

Issue Opening (When Available)

If planning reveals blockers or prerequisites that need tracking:

  • Check for Gitea/GitHub availability
  • Open issues ONLY for:
    • External dependencies
    • Prerequisites that aren't in scope
    • Decisions needed before execution
  • Link issue IDs to relevant tasks

Validation Questions

Before finalizing, ask:

  1. Ambiguity check: Could a JR developer understand every task without questions?
  2. Completeness: Are all prerequisites and dependencies listed?
  3. Executability: Does each task specify exact files and acceptance criteria?
  4. Scope creep: Is ops/deploy work leaking into the plan?

Output Format

After plan generation, output:

✓ Plan written to: .artifacts/plan/YYYY-MM-DD_HH-MM-SS_<topic>.md
✓ Milestones: 4
✓ Tasks: 12
✓ Git state: <short_sha>

Next step: Execute phase using the generated plan path

Examples

Example Plan Entry
markdown
## Task T004: Add rate limiting to API endpoints

**Summary**: Implement token-bucket rate limiting for public API endpoints

**Files**:
- src/middleware/rateLimit.ts (new)
- src/app.ts (modify)

**Changes**:
1. Create src/middleware/rateLimit.ts with TokenBucket class
   - Constructor takes capacity and refillRate
   - consume(tokens) method returns true if allowed
2. Add rateLimit instance to src/app.ts
3. Apply to /api/public/* routes only

**Acceptance Test**:
- Send 100 requests in 1 second to /api/public/data
- First 60 succeed (200)
- Next 40 fail (429)
- Headers include X-RateLimit-Remaining

**Dependencies**: T001 (Express app setup)
**Milestone**: M2
**Estimate**: 2 hours

Subagent Usage (Sparingly)

Only spawn subagents if:

  • Research doc is large (>500 lines)
  • Need to map tasks to existing codebase structure
  • Need parallel analysis of multiple subsystems

Typical subagents:

  • codebase-analyzer: Find where new code fits
  • context-synthesis: Extract structured tasks from prose research

Default: Don't use subagents. Trust the research doc.

Handoff

After writing the plan document to .artifacts/plan/, proceed to execute-phase if the next step is the Execute phase.

© alchemiststudiosDOTai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/plan-phase of alchemiststudiosDOTai/harness-engineering.

Open the folder on GitHubat commit 7a9fa15

Compare with similar skills

Plan Phase next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Plan Phase compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Plan Phase this skillalchemiststudiosDOTai/harness-engineering105—~1.8kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers296k2 repos~5.1kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills103k6 repos~3.8kAutomated safety check: PassMIT
OpenSpec Guided OnboardingFission-AI/OpenSpec71k1 repos~4.5kAutomated safety check: PassMIT
Writing Plansgeeksblabla/stateofdev.ma16357 repos~661Automated safety check: PassNone
Subagent Driven DevelopmentAsvarox/allkaraoke26138 repos~1.2kAutomated safety check: PassNone

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Categories

Questions about Plan Phase

What does Plan Phase do?

Generate execution-ready implementation plans from research docs - planning ONLY, no fixing or verifying. Plan Phase is an agent skill from alchemiststudiosDOTai/harness-engineering. Generate execution-ready implementation plans from research docs - planning ONLY, no fixing or verifying.

When should I use Plan Phase?

Plan Phase fits situations like: tasks that involve Planning.

How do I install Plan Phase in Claude Code?

Run `npx skills add alchemiststudiosDOTai/harness-engineering --skill plan-phase -a claude-code`. Or copy the skill folder (skills/plan-phase in alchemiststudiosDOTai/harness-engineering) into .claude/skills/plan-phase in your project. Claude Code loads it when a task matches its description.

How do I install Plan Phase in Codex?

Run `npx skills add alchemiststudiosDOTai/harness-engineering --skill plan-phase -a codex`. Or copy the skill folder (skills/plan-phase in alchemiststudiosDOTai/harness-engineering) into .agents/skills/plan-phase in your project. Codex loads it when a task matches its description.

Can I use Plan Phase in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alchemiststudiosDOTai/harness-engineering --skill plan-phase -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/plan-phase, .gemini/skills/plan-phase, .github/skills/plan-phase and .opencode/skills/plan-phase in your project.

What does Plan Phase need to run?

Going by SKILL.md and its folder, Plan Phase needs the command-line tools its instructions call (git). Its frontmatter pre-approves these tools: Read, Edit, Write, Bash(git:*), Bash(grep:*), Bash(sed:*), Bash(awk:*), Bash(jq:*), Bash(date:*), Bash(find:*).

Does Plan Phase access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Plan Phase safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Plan Phase use?

Plan Phase is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Plan Phase use?

About 1.8k tokens (SKILL.md is roughly 7.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Plan Phase?

Skills that share tags, products or a category with Plan Phase: Executing Plans Inline (obra/superpowers, 296k stars), Interview Me (addyosmani/agent-skills, 103k stars), OpenSpec Guided Onboarding (Fission-AI/OpenSpec, 71k stars) and Writing Plans (geeksblabla/stateofdev.ma, 163 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Plan Phase?

alchemiststudiosDOTai (a GitHub organization) maintains it in alchemiststudiosDOTai/harness-engineering, which has 105 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on March 17, 2026.

Source: alchemiststudiosDOTai/harness-engineering on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.