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planning

Break down a coding task into a structured implementation plan with clear steps, file identification, and risk assessment.

Skill by langchain-aiOfficial

IndexedMIT★ 30,550
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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.

npx agentmarket install skill/langchain-ai-planning

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About

Break down a coding task into a structured implementation plan with clear steps, file identification, and risk assessment.

Use cases: devops, productivity, agent-building, agent-orchestration

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

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

Tools
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/planning

What's inside

Skill name
planning
Description
Break down a coding task into a structured implementation plan with clear steps, file identification, and risk assessment.
License
MIT
Instructions
50 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Planning Skill

Use this skill when starting a new coding task to create a thorough implementation plan.

## Steps

### 1. Understand the Task
- Read the issue/task description completely
- Identify the expected outcome and acceptance criteria
- Note any constraints or requirements mentioned

### 2. Explore the Codebase
- Find the repository root and read the project structure
- Identify the tech stack (language, framework, test runner)
- Read README, CONTRIBUTING, or similar docs if they exist
- Find existing tests to understand testing patterns

### 3. Identify Relevant Files
- Use `grep` to find code related to the task
- Read the most relevant files (entry points, related modules)
- Identify which files need to be modified vs. created
- Check for existing patterns you should follow

### 4. Write the Plan
Use `write_todos` to create a structured plan:

```
write_todos([
    "1. <specific change in specific file>",
    "2. <next specific change>",
    "3. Write tests for <feature>",
    "4. Run test suite and fix failures",
    "5. Review all changes"
])
```

### 5. Assess Risks
- Are there breaking changes?
- Are there edge cases to handle?
- Does this affect other parts of the codebase?
- Flag anything uncertain for review

## Guidelines

- Plans should have 3-10 concrete steps
- Each step should be specific enough to execute without further planning
- Include test writing and test running as explicit steps
- End with a review/verification step

From langchain-ai/deepagents, MIT.

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Signals

Stars
30,550
Forks
4,302
Open issues
163
Last commit (this folder)
Apr 9, 2026 (6 months ago)
Last release
Oct 23, 2026 (4 days ago)

From GitHub (fetched Oct 24, 2026).

Details

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

More from langchain-ai

Cite this page

planning skill. Agent Mart. https://agentmart.dev/skills/langchain-ai-planning (last updated 2026-10-24)