planning
Break down a coding task into a structured implementation plan with clear steps, file identification, and risk assessment.
Skill by langchain-aiOfficial
Install
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
Use cases: devops, productivity, agent-building, agent-orchestration
Reviews
Write a reviewNo 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
- No tools found
- Secrets
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- Install scripts
- None found
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 stepFrom 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
- Repository
- github.com/langchain-ai/deepagents
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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schema-exploration
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Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database.
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Cite this page
planning skill. Agent Mart. https://agentmart.dev/skills/langchain-ai-planning (last updated 2026-10-24)