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Add PRP story task template and reorganize PRP commands (#508)
* Reorganize PRP commands and add story task template - Move PRP commands to dedicated subdirectories - Add new agent definitions for codebase analysis and library research - Create story task PRP template for user story implementation - Rename prp-base.md to prp_base.md for consistency * Update .claude/agents/library-researcher.md Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> * Update .claude/commands/prp-claude-code/prp-story-task-create.md Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> * Update .claude/commands/prp-claude-code/prp-story-task-create.md Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> * Update PRPs/templates/prp_story_task.md Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> * Update PRPs/templates/prp_story_task.md Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> --------- Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
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---
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description: "Convert user story/task into executable PRP with deep codebase analysis"
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---
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# Create Story PRP from User Story/Task
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## Story/Task: $ARGUMENTS
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## Mission
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Transform a user story or task into a **tactical implementation PRP** through systematic codebase analysis and task decomposition.
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We do not write any code in this step, the goal is to create a detailed context engineered implementation plan for the implementation agent.
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**Key Principle**: We must first gather the context about the story/task before proceeding with the analysis.
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When we understand the story/task, we can proceed with the codebase analysis. We systematically dig deep into the codebase to gather intelligence and identify patterns and implementation points. We then use this information to create a PRP that can be executed by a coding agent.
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The contents of the created PRP should encapsulate all the information the agent needs to complete the story/task in one pass.
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Remember that subagents will only receive details from you; the user cannot interact with them directly. Therefore, include all relevant context in the subagent prompt and TODO.
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Create detailed TODOs and spawn parallel subagents to analyze (use specialized subagents when appropriate).
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## Analysis Process
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### Phase 1: Story Decomposition
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Analyze the story to determine:
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- **Story/Task Type**: Feature/Bug/Enhancement/Refactor
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- **Complexity**: Low, Medium, High
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- **Affected Systems**: Which components/services need changes
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Get a deep understanding about the story/task before proceeding so that you can effectively guide the rest of the process.
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### Phase 2: Codebase Intelligence Gathering
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**1. Project Structure Analysis**
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- Detect primary language(s) and frameworks
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- Map directory structure and conventions to identify integration points for the story/task
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- Identify service/component boundaries
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- Find configuration files and environment setup
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**2. Pattern Recognition**
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- Search for similar implementations in codebase
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- Identify coding conventions (naming, structure, error handling) start in CLAUDE.md AGENTS.md or relevant rules files such as .cursorrules
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- Extract common patterns for the story's domain that should be added to the PRP as context for the implementation agent.
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- Note anti-patterns to avoid
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**3. Dependency Analysis**
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- Catalog external libraries used if relevant to the story/task (check package.json, pyproject.toml, go.mod, etc.)
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- Understand how libraries are integrated
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- Find relevant documentation in PRPs/ai_docs/ if shared, ai_docs directory is used by the user to paste in relevant additional context that may be relevant to our story/task
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**4. Testing Patterns**
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- Identify test framework and structure
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- Find similar test examples and test setup
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- Suggest test cases and scenarios
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**5. Integration Points**
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- Identify files that will need updates
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- Identify if new files needs to be created and where to create them
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- Find router/API registration patterns
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- Understand database/model patterns if relevant
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### Phase 3: Think harder about the story and its components.
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Really think hard about everything you just learned during the research phases.
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### Phase 4: PRP Task Generation
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Transform analysis into concrete tasks:
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Read and understand the template @PRPs/templates/prp_story_task.md
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**Task Rules**:
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1. Each task is atomic and independently testable
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2. Tasks are ordered by dependency
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3. Use action verbs that are information dense: CREATE, UPDATE, ADD, REMOVE, REFACTOR, MIRROR
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4. Include specific implementation details from codebase analysis
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5. Every task has an executable validation command
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**Task Action Types**:
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We use the concept of information dense keywords to describe the action to be taken, below is a guidance.
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But you can use your own words to describe the action to be taken as long as you follow this same principle.
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Examples:
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- **CREATE**: New files/components
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- **UPDATE**: Modify existing files
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- **ADD**: Insert new functionality into existing code
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- **REMOVE**: Delete deprecated code
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- **REFACTOR**: Restructure without changing behavior
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- **MIRROR**: Mirror existing pattern or functionality that exists elsewhere in the codebase
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### Phase 5: Validation Design
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For each task, design validation that:
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- Can run immediately after task completion
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- Provides clear pass/fail feedback
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- Uses project-specific commands discovered in analysis
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## Quality Criteria
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### Task Clarity
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- [ ] The PRP is clear and concise and follows KISS principle
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- [ ] Each task has clear action and target
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- [ ] Implementation details reference specific patterns
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- [ ] Validation commands are executable
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### Context Completeness
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- [ ] All necessary patterns identified
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- [ ] External library usage documented
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- [ ] Integration points mapped
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- [ ] External context references populated
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### Story Coverage
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- [ ] All acceptance criteria addressed
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- [ ] Edge cases considered
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- [ ] Error handling included where needed
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## Output
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Save as: `PRPs/story_{kebab-case-summary}.md`
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## Success Metrics
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**Implementation Ready**: Another developer could execute these tasks without additional context
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**Validation Complete**: Every task has at least one working validation command
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**Pattern Consistent**: Tasks follow existing codebase conventions
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