feature-planning
Analyzes feature requests to create detailed, actionable implementation plans with specific tasks.
Install
mkdir -p .claude/skills/feature-planning && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5112" && unzip -o skill.zip -d .claude/skills/feature-planning && rm skill.zipInstalls to .claude/skills/feature-planning
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Break down feature requests into detailed, implementable plans with clear tasks. Use when user requests a new feature, enhancement, or complex change.Key capabilities
- →Analyze feature requirements
- →Identify architectural components and dependencies
- →Break down features into sequential tasks
- →Define testing and integration strategies
How it works
The skill guides the user through a structured planning process, including codebase exploration, component identification, and task sequencing.
Inputs & outputs
When to use feature-planning
- →Plan new feature implementation
- →Break down complex architecture changes
- →Define database and UI requirements for new features
About this skill
Feature Planning
Systematically analyze feature requests and create detailed, actionable implementation plans.
When to Use
- Requests new feature ("add user authentication", "build dashboard")
- Asks for enhancements ("improve performance", "add export")
- Describes complex multi-step changes
- Explicitly asks for planning ("plan how to implement X")
- Provides vague requirements needing clarification
Planning Workflow
1. Understand Requirements
Ask clarifying questions:
- What problem does this solve?
- Who are the users?
- Specific technical constraints?
- What does success look like?
Explore the codebase:
Use Task tool with subagent_type='Explore' and thoroughness='medium' to understand:
- Existing architecture and patterns
- Similar features to reference
- Where new code should live
- What will be affected
2. Analyze & Design
Identify components:
- Database changes (models, migrations, schemas)
- Backend logic (API endpoints, business logic, services)
- Frontend changes (UI, state, routing)
- Testing requirements
- Documentation updates
Consider architecture:
- Follow existing patterns (check CLAUDE.md)
- Identify reusable components
- Plan error handling and edge cases
- Consider performance implications
- Think about security and validation
Check dependencies:
- New packages/libraries needed
- Compatibility with existing stack
- Configuration changes required
3. Create Implementation Plan
Break feature into discrete, sequential tasks:
## Feature: [Feature Name]
### Overview
[Brief description of what will be built and why]
### Architecture Decisions
- [Key decision 1 and rationale]
- [Key decision 2 and rationale]
### Implementation Tasks
#### Task 1: [Component Name]
- **File**: `path/to/file.py:123`
- **Description**: [What needs to be done]
- **Details**:
- [Specific requirement 1]
- [Specific requirement 2]
- **Dependencies**: None (or list task numbers)
#### Task 2: [Component Name]
...
### Testing Strategy
- [What types of tests needed]
- [Critical test cases to cover]
### Integration Points
- [How this connects with existing code]
- [Potential impacts on other features]
Include specific references:
- File paths with line numbers (
src/utils/auth.py:45) - Existing patterns to follow
- Relevant documentation
4. Review Plan with User
Confirm:
- Does this match expectations?
- Missing requirements?
- Adjust priorities or approach?
- Ready to proceed?
5. Execute with plan-implementer
Launch plan-implementer agent for each task:
Task tool with:
- subagent_type: 'plan-implementer'
- description: 'Implement [task name]'
- prompt: Detailed task description from plan
Execution strategy:
- Implement sequentially (respect dependencies)
- Verify each task before next
- Adjust plan if issues discovered
- Let test-fixing skill handle failures
- Let git-pushing skill handle commits
Best Practices
Planning:
- Start broad, then specific
- Reference existing code patterns
- Include file paths and line numbers
- Think through edge cases upfront
- Keep tasks focused and atomic
Communication:
- Explain architectural decisions
- Highlight trade-offs and alternatives
- Be explicit about assumptions
- Provide context for future maintainers
Execution:
- Implement one task at a time
- Verify before moving forward
- Keep user informed
- Adapt based on discoveries
Integration
- plan-implementer agent: Receives task specs, implements
- test-fixing skill: Auto-triggered on test failures
- git-pushing skill: Triggered for commits
When not to use it
- →When the task is a trivial bug fix or minor configuration change
Limitations
- →Requires user input for requirements clarification
- →Effectiveness depends on the accuracy of codebase exploration
How it compares
It forces a systematic breakdown of work into atomic tasks with clear dependencies, rather than jumping directly into implementation.
Compared to similar skills
feature-planning side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| feature-planning (this skill) | 1 | 9mo | No flags | Intermediate |
| drift-analysis | 2 | 5mo | No flags | Intermediate |
| validate-implementation-plan | 0 | 2mo | No flags | Advanced |
| create-plan | 36 | 8mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
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