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plan

Turn conversation context into a Product Requirements Document (PRD) and break it down into independently-grabbable tracking issues.

Skill by drlove2002

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Turn conversation context into a Product Requirements Document (PRD) and break it down into independently-grabbable tracking issues. Use when the user wants to plan a feature, write a spec, or break a project into tickets.

Use cases: documents, writing

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/plan

What's inside

Skill name
plan
Description
Turn conversation context into a Product Requirements Document (PRD) and break it down into independently-grabbable tracking issues. Use when the user wants to plan a feature, write a spec, or break a project into tickets.
License
MIT
Instructions
104 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Plan

Synthesize the conversation and codebase context into a PRD, then break it into vertical-slice tracking issues.

## 1. Context

Explore the repo to understand the current state. Sketch the major modules to build or modify. Look for opportunities to extract deep modules testable in isolation.

**If the conversation already contains scouted details (file paths, API formats, exact commands) — don't re-scout. Use what you have.**

## 2. Write the PRD

Save as `plan/NNNN-prd-....md` in the active repo root (the directory pi is running in, not a sub-project). Frontmatter:
```yaml
---
id: NNNN
title: PRD: ...
kind: prd
status: needs-triage
blocked_by: []
created: YYYY-MM-DD
---
```

Sections:
```markdown
## Problem Statement
The problem from the user's perspective.

## Solution
The solution from the user's perspective.

## User Stories
Numbered list (As an <actor>, I want <feature>, so that <benefit>).

## Implementation Decisions
- Modules built/modified
- Interfaces modified
- Architectural decisions
- API contracts
- If concrete details exist (file paths, endpoints, commands): include them. The PRD is the canonical record.

## Testing Decisions
- What makes a good test here
- Which modules will be tested

## Out of Scope
```

**If the conversation has a concrete plan** (exact files, APIs, Nix expressions): preserve those details. The PRD is the canonical record. Don't strip specifics just because a template says "abstract."

**If still at the problem/idea stage**: keep it abstract. No file paths.

## 3. Ask About Breakdown

Use `ask_user_decisions`:
- Q1: "Break this PRD into tracking issues now?" (Yes / No, let me review first)
- Q2: "How granular?" (Coarse milestones / Granular vertical slices / Extremely granular commits)

If "No", stop. If "Yes", proceed.

## 4. Break into Vertical Slices

Draft vertical slices (tracer bullets) that cut through ALL layers end-to-end. Do not slice by layer. Each slice must be deliverable on its own.

Classify each:
- **AFK**: Can be implemented and merged without human interaction.
- **HITL**: Needs human-in-the-loop decisions.

Quiz the user on titles, type, blockers, user stories covered. Wait for approval.

## 5. Create Tracking Issues

For each approved slice, create `plan/NNNN-....md` in the active repo root, in dependency order. Frontmatter:
```yaml
---
id: NNNN
title: ...
kind: enhancement
status: ready-for-agent
slice_type: AFK
blocked_by: []
created: YYYY-MM-DD
---
```

Sections:
```markdown
## Parent
`plan/NNNN-prd-....md`

## What to build
Concise description of this vertical slice end-to-end.

## Acceptance criteria
- [ ] Criterion

## Blocked by
None (or list issue IDs)
```

If concrete details exist in the PRD, include them in each issue — the agent picking up the issue should have everything needed without re-reading the PRD.

From drlove2002/ai-config, MIT.

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Last commit (this folder)
Jul 17, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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plan skill. Agent Mart. https://agentmart.dev/skills/drlove2002-plan (last updated 2026-10-24)