plan-mode
Guide for creating structured plans with numbered steps and quality gates
When & Why to Use This Skill
This Claude skill provides a rigorous framework for generating structured, actionable implementation plans for complex technical workflows. By enforcing a standardized format—comprising deep situational analysis, strategic approach selection, atomic step-by-step execution, and mandatory quality gates—it ensures that software development and automation tasks are planned with high precision, minimizing errors and improving project transparency.
Use Cases
- Complex Feature Implementation: Breaking down large-scale coding requirements into 3-10 manageable, sequential steps that specify file modifications and tool dependencies.
- API and Tool Integration: Mapping out the integration of third-party services by defining necessary wrappers, configuration updates, and mock-testing strategies.
- System Refactoring and Migration: Creating a safe roadmap for code changes that includes mandatory validation gates like unit testing, type checking, and dry runs to prevent regressions.
- Automated Workflow Orchestration: Structuring the logic for multi-step agentic processes, ensuring that each phase passes specific quality benchmarks before proceeding.
| name | plan-mode |
|---|---|
| description | Guide for creating structured plans with numbered steps and quality gates |
Plan Mode Skill
Use this skill when creating a plan for workflow implementation.
Plan Structure
Your plan MUST follow this structure:
1. Analysis
- What needs to be done and why?
- What is the current state vs. desired state?
- What are the constraints or requirements?
2. Approach
- High-level strategy for implementation
- Key design decisions
- Which patterns or libraries to use
3. Steps
- Numbered, concrete steps (3-10 steps typically)
- Each step should be specific and actionable
- Include which files will be modified
- Mention which tools/imports are needed
- Consider dependencies between steps
4. Quality Gates
- List gates that should pass after execution
- Always include:
validate,dry - Add optional gates if needed:
pytest,ruff,typecheck
Example Plan
## Analysis
The workflow needs to fetch stock prices from Yahoo Finance API to provide
real-time data. Currently, there's no data fetching capability.
## Approach
We will create a new tool `yahoo_finance` in tools/ that wraps the yfinance
library, then integrate it into the workflow using a @step decorator.
## Steps
1. Create tools/yahoo_finance/tool.py with fetch_stock_price() function
2. Add yfinance dependency to tool's config.yaml
3. Update workflow run.py to import yahoo_finance
4. Add @step("fetch_prices") that calls yahoo_finance.fetch_stock_price()
5. Update dry_run.py with mock stock data for testing
6. Add test case in test.py for the fetch step
## Quality Gates
- validate: Structural validation must pass
- dry: Dry run with mocks must complete successfully
- pytest: All unit tests must pass
Tips
- Keep steps atomic and sequential
- Don't skip validation in your plan
- Always consider the dry run path
- Think about error cases and edge conditions
- Reference existing code patterns when possible