do-plan — planification de fonctionnalités do-plan, community, planification de fonctionnalités, ide skills, méthodologie Shape Up, intégration GitHub, support Markdown, planification de projets, outils de planification

v1.0.0

À propos de ce Skill

Parfait pour les agents de développement ayant besoin d'une planification de fonctionnalités structurée et d'un suivi des problèmes GitHub. do-plan est un outil de planification de fonctionnalités qui crée des plans structurés et définit les problèmes et les solutions

Fonctionnalités

Crée des plans de fonctionnalités structurés en Markdown
Définit les problèmes et les solutions suivant la méthodologie Shape Up
Crée ou lie un problème GitHub pour suivi
Envoie le plan pour révision avec des questions ouvertes
Utilise le chemin `docs/plans/` pour stocker les plans

# Core Topics

tomcounsell tomcounsell
[7]
[4]
Updated: 3/11/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
60
Canonical Locale
en
Detected Body Locale
en

Parfait pour les agents de développement ayant besoin d'une planification de fonctionnalités structurée et d'un suivi des problèmes GitHub. do-plan est un outil de planification de fonctionnalités qui crée des plans structurés et définit les problèmes et les solutions

Pourquoi utiliser cette compétence

Permet aux agents de générer des plans d'analyse de contenu complets en utilisant la méthodologie Shape Up, en créant des documents Markdown et en liant les problèmes GitHub pour une gestion et un suivi de projet sans problème, en exploitant les API GitHub et le formatage Markdown.

Meilleur pour

Parfait pour les agents de développement ayant besoin d'une planification de fonctionnalités structurée et d'un suivi des problèmes GitHub.

Cas d'utilisation exploitables for do-plan

Automatisation de la génération de plans de fonctionnalités pour les projets de développement
Création de documents de planification structurés au format Markdown
Liaison des problèmes GitHub pour le suivi et la gestion de projet

! Sécurité et Limitations

  • Nécessite un accès à l'API GitHub pour le suivi des problèmes
  • Limité à la méthodologie Shape Up pour la planification des fonctionnalités
  • Le format Markdown est requis pour les documents de planification

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is do-plan?

Parfait pour les agents de développement ayant besoin d'une planification de fonctionnalités structurée et d'un suivi des problèmes GitHub. do-plan est un outil de planification de fonctionnalités qui crée des plans structurés et définit les problèmes et les solutions

How do I install do-plan?

Run the command: npx killer-skills add tomcounsell/ai/do-plan. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for do-plan?

Key use cases include: Automatisation de la génération de plans de fonctionnalités pour les projets de développement, Création de documents de planification structurés au format Markdown, Liaison des problèmes GitHub pour le suivi et la gestion de projet.

Which IDEs are compatible with do-plan?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for do-plan?

Nécessite un accès à l'API GitHub pour le suivi des problèmes. Limité à la méthodologie Shape Up pour la planification des fonctionnalités. Le format Markdown est requis pour les documents de planification.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add tomcounsell/ai/do-plan. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use do-plan immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

do-plan

Install do-plan, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Make a Plan (Shape Up Methodology)

Creates structured feature plans in docs/plans/ following Shape Up principles: narrow the problem, set appetite, rough out the solution, identify rabbit holes, and define boundaries.

What this skill does

  1. Takes a vague or specific request and narrows it into a concrete plan
  2. Writes a structured plan document in docs/plans/{slug}.md
  3. Creates or links a GitHub issue for tracking
  4. Sends the plan for review with open questions

When to load sub-files

Sub-fileLoad when...
PLAN_TEMPLATE.mdWriting the plan document (copy the template into docs/plans/{slug}.md)
SCOPING.mdThe request is vague, a grab-bag, or needs narrowing before planning
EXAMPLES.mdDeciding how to respond to a user request (vague vs. grab-bag vs. good)

When to Use

  • Planning a new feature
  • Updating an existing plan
  • User says "make a plan", "plan this out", "flesh out the idea"
  • Scoping unclear or large requests
  • Before starting significant implementation work

Session Progress Tracking

Extract the session ID from the conversation context. The bridge injects SESSION_ID: {id} into enriched messages. Look for this pattern and store it:

bash
1# Extract SESSION_ID from context 2# Look for a line like "SESSION_ID: abc123" in the message you received 3# Store in variable: SESSION_ID="abc123" 4 5# Mark PLAN stage as in_progress at the start 6python -m tools.session_progress --session-id "$SESSION_ID" --stage PLAN --status in_progress 2>/dev/null || true

After the plan is committed and tracking issue is linked:

bash
1# Mark PLAN stage complete and set links 2python -m tools.session_progress --session-id "$SESSION_ID" --stage PLAN --status completed --issue-url "$ISSUE_URL" --plan-url "$PLAN_URL" 2>/dev/null || true

Where:

  • $ISSUE_URL is the full GitHub issue URL (e.g., https://github.com/owner/repo/issues/42)
  • $PLAN_URL is the full plan document URL (e.g., https://github.com/owner/repo/blob/main/docs/plans/{slug}.md)

Quick Start Workflow

Phase 1: Flesh Out at High Level

  1. Understand the request - What's being asked?

  2. Narrow the problem - Challenge vague requests (see SCOPING.md if needed)

  3. Blast radius analysis - If the change involves code modifications, run the code impact finder:

    bash
    1.venv/bin/python -m tools.code_impact_finder "PROBLEM_STATEMENT_HERE"

    Use results to inform plan sections:

    • impact_type="modify" -> Solution section
    • impact_type="dependency" -> Risks section
    • impact_type="test" -> Success Criteria section
    • impact_type="config" -> Solution section
    • impact_type="docs" -> Documentation section
    • Tangentially coupled files (< 0.5 relevance) -> Rabbit Holes section Skip if the change is purely documentation or process-related.
  4. Prior art search - Search closed issues and merged PRs for related work. This prevents proposing solutions that have already been tried (and failed) or re-solving problems that already have working implementations.

    bash
    1# Search closed issues for related keywords 2gh issue list --state closed --search "KEYWORDS_HERE" --limit 10 --json number,title,closedAt,url 3# Search merged PRs for related work 4gh pr list --state merged --search "KEYWORDS_HERE" --limit 10 --json number,title,mergedAt,url

    Use results to fill the Prior Art section in the plan. If multiple prior attempts addressed the same problem, also fill the Why Previous Fixes Failed section. Skip if: Small appetite AND greenfield work (no existing code being modified).

4.5. xfail test search - For bug fixes, search the test suite for xfail markers related to the bug. These represent tests that document the bug but are marked as expected failures.

bash
1# Search for xfail markers in tests (both decorator and runtime forms) 2grep -rn 'pytest.mark.xfail\|pytest.xfail(' tests/ --include="*.py" | head -20

For each xfail found that relates to the bug being fixed:

  • Add a task to the plan's Step by Step Tasks: "Convert TC{N} xfail to hard assertion"
  • Document the test location in the Success Criteria section
  • When the fix lands, the test should pass and the xfail marker must be removed IMPORTANT: Pay special attention to runtime pytest.xfail() calls inside test bodies. Unlike @pytest.mark.xfail decorators, runtime xfails short-circuit the test before reaching assertions — so they silently pass even after the bug is fixed. These are invisible to pytest's XPASS detection and MUST be explicitly listed as conversion targets in the plan. Skip if: Not a bug fix, or no xfail tests found related to this bug.
  1. Data flow trace - For changes involving multi-component interactions, trace the data flow end-to-end through the system. Start from the entry point (user action, API call, event trigger) and follow through each component, transformation, and storage layer.

    bash
    1# Read the entry point file 2# Follow imports and function calls through the chain 3# Document each transformation and handoff between components

    Use results to fill the Data Flow section in the plan. This is critical for changes that span multiple modules -- it prevents fixes applied at the wrong layer. Skip if: Change is isolated to a single file/function, or is purely documentation/config.

  2. Failure analysis - If the prior art search (step 4) found previous attempts to fix the same problem, analyze why each attempt failed or was incomplete. Look for patterns:

    • Was the root cause correctly identified?
    • Was the fix applied at the right architectural layer?
    • Did it address a symptom instead of the underlying cause?
    • Did it introduce new problems while fixing the original? Use results to fill the Why Previous Fixes Failed section (conditional -- only include in the plan if prior failed fixes exist). Skip if: No prior fixes found, or this is greenfield work.
  3. Set appetite - Small / Medium / Large (see SCOPING.md for sizing guidance)

  4. Rough out solution - Key components and flow, stay abstract

  5. Race condition analysis - If the solution involves async operations, shared mutable state, or cross-process data flows, identify timing hazards. For each: specify what data/state must be established before dependent operations read it, and how the implementation prevents races. Skip if the change is purely synchronous and single-threaded.

Phase 2: Write Initial Plan

Classification is mandatory - every plan MUST include a type: field (bug, feature, or chore).

Auto-Classification: When a message arrives via Telegram, the bridge auto-classifies it. Check if classification_type is available from the session context. If available, use it as the default type: value. The user can always override.

Create docs/plans/{slug}.md using the template from PLAN_TEMPLATE.md.

After writing the plan, push it to main first, then link it to an existing issue OR create a new one.

bash
1# Resolve repo identity from git 2REPO=$(gh repo view --json nameWithOwner -q .nameWithOwner) 3 4# Push plan to main before linking 5git add docs/plans/{slug}.md && git commit -m "Plan: {Feature Name}" && git push

Check for existing issue first! If the plan was created in response to an existing GitHub issue (e.g., "make a plan for issue #42"), do NOT create a new issue. Instead:

  1. Add the "plan" label and prepend the plan link to the issue body
  2. Update the plan frontmatter tracking: field with the existing issue URL
bash
1EXISTING_ISSUE=42 2gh issue edit $EXISTING_ISSUE --add-label "plan" 3EXISTING_BODY=$(gh issue view $EXISTING_ISSUE --json body -q .body) 4PLAN_LINK="https://github.com/${REPO}/blob/main/docs/plans/{slug}.md" 5gh issue edit $EXISTING_ISSUE --body "**Plan:** ${PLAN_LINK} 6 7${EXISTING_BODY}"

Only create a NEW issue if the plan was initiated from scratch (not from an existing issue).

Before creating, check config/projects.json for the current project:

  • If notion key exists -> create a Notion task (use Notion MCP tools)
  • If only github key exists -> create a GitHub issue (use gh CLI)
  • If neither -> skip tracking, just use the plan doc

Extract type: from plan frontmatter before creating:

bash
1TYPE=$(grep '^type:' docs/plans/{slug}.md | sed 's/type: *//' | tr -d ' ') 2if [ -z "$TYPE" ]; then 3 echo "ERROR: Plan must have a 'type:' field in frontmatter (bug, feature, or chore)" 4 exit 1 5fi 6 7gh issue create \ 8 --repo ${REPO} \ 9 --title "[Plan] {Feature Name}" \ 10 --label "plan" \ 11 --label "$TYPE" \ 12 --body "$(cat <<EOF 13**Plan:** https://github.com/${REPO}/blob/main/docs/plans/{slug}.md 14 15**Type:** {type} | **Appetite:** {appetite} | **Status:** Planning 16 17--- 18This issue is for tracking and discussion. The plan document is the source of truth. 19EOF 20)"

For Notion tasks, use MCP tools to create a page with Title, Status, Type, and link to the plan document.

After linking or creating: update the plan's tracking: field and commit.

Phase 2.7: Sync Issue Comments into Plan

Before finalizing, check the tracking issue for comments that contain feedback, scope changes, or new context that should be incorporated into the plan.

bash
1# Extract issue number from plan frontmatter tracking URL 2ISSUE_NUM=$(grep '^tracking:' docs/plans/{slug}.md | grep -oP '/issues/\K\d+') 3 4if [ -n "$ISSUE_NUM" ]; then 5 # Get all comments with IDs, sorted chronologically 6 gh api repos/{owner}/{repo}/issues/${ISSUE_NUM}/comments \ 7 --jq '.[] | {id: .id, author: .user.login, created: .created_at, body: .body}' 2>/dev/null 8 9 # Get the latest comment ID 10 LATEST_COMMENT_ID=$(gh api repos/{owner}/{repo}/issues/${ISSUE_NUM}/comments \ 11 --jq '.[-1].id // empty' 2>/dev/null) 12 13 # Get the plan's recorded last_comment_id 14 PLAN_COMMENT_ID=$(grep '^last_comment_id:' docs/plans/{slug}.md | sed 's/last_comment_id: *//') 15fi

If new comments exist (LATEST_COMMENT_ID != PLAN_COMMENT_ID):

  1. Read each comment since the plan's last_comment_id
  2. Incorporate relevant feedback into the plan (scope changes, new requirements, corrections)
  3. Update last_comment_id: in the plan frontmatter to LATEST_COMMENT_ID
  4. Commit the updated plan

If no tracking issue or no comments: Skip this step.

Phase 3: Critique and Enumerate Questions

  1. Review assumptions - What did I assume that might be wrong?
  2. Identify gaps - What's unclear or risky?
  3. Enumerate questions - List all questions needing supervisor input
  4. Add questions to plan - Append to "Open Questions" section
  5. Pre-send checklist:
    • Plan committed AND pushed to main
    • GitHub issue has **Plan:** https://github.com/${REPO}/blob/main/docs/plans/{slug}.md
    • Plan frontmatter has tracking: set to the issue URL
  6. Send reply:
Plan draft created: docs/plans/{slug}.md

Tracking: {GitHub issue URL or Notion page URL}

I've made the following key assumptions:
- [Assumption 1]
- [Assumption 2]

Please review the Open Questions section at the end of the plan and provide answers so I can finalize it.

Phase 4: Finalize Plan

After receiving answers:

  1. Update plan - Incorporate feedback, remove Open Questions section
  2. Mark as finalized - Update frontmatter: status: Ready
  3. Suggest implementation prompt:
Plan finalized: docs/plans/{slug}.md

When you're ready to implement, use this prompt:

---
Implement the plan in docs/plans/{slug}.md

Follow the solution approach, stay within the appetite, and avoid the identified rabbit holes. Check off success criteria as you complete them.
---

Output Location

All plans go to: docs/plans/{slug}.md

Use snake_case for slugs: async_meeting_reschedule.md, dark_mode_toggle.md, api_response_caching.md

Branch Workflow

Plans are written directly on the main branch. The plan document itself is just a document -- no feature branch needed.

When the plan is executed (via /do-build), the build skill creates a feature branch, does the work there, and opens a PR.

Status Tracking

Status and classification are tracked in the plan document's YAML frontmatter.

Required Frontmatter Fields:

  • status: - Current state of the plan
  • type: - Classification (bug, feature, or chore) - MANDATORY

Status Values:

  • Planning - Initial draft being created
  • Ready - Finalized and ready for implementation
  • In Progress - Being implemented
  • Complete - Shipped to production
  • Cancelled - Not pursuing this

Update status as work progresses. Keep all tracking in the plan document itself.

Tracking issue lifecycle:

  • When plan status changes to Ready or In Progress, update the GitHub issue / Notion task status accordingly
  • When plan status changes to Complete, close the GitHub issue (gh issue close) or mark the Notion task as done
  • When plan status changes to Cancelled, close the issue with a comment explaining why

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