Prp Structure

Documents

prp-structure

Prp Structure is an Agent Skill for documents published in the majiayu000/claude-skill-registry repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Provides the standard structure and format for Prompt-Response-Plan (PRP) documents. Use when creating, formatting, or validating PRP documents for systematic problem-solving workflows.

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Prompt to paste

Inspect the Agent Skill at https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/documents/prp-structure/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/prp-structure, but wait for my approval before writing files or running scripts.

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PRP Structure Skill

This skill defines the standard structure for Prompt-Response-Plan (PRP) documents used in context engineering workflows.

PRP Document Structure

A well-formed PRP contains three main sections:

1. Prompt Section

The initial problem statement or request that initiates the workflow:

## Prompt

[Clear, concise description of the problem or task]

### Context
- Background information
- Relevant constraints
- Success criteria

2. Response Section

Analysis and proposed approach:

## Response

### Problem Analysis
- Key challenges identified
- Dependencies and prerequisites
- Risk factors

### Proposed Solution
- High-level approach
- Alternative approaches considered
- Rationale for chosen approach

3. Plan Section

Detailed execution plan with trackable steps:

## Plan

### Implementation Steps

1. [ ] Step 1: [Description]
   - Sub-tasks if needed
   - Expected outcome

2. [ ] Step 2: [Description]
   - Dependencies: Step 1
   - Expected outcome

3. [ ] Step 3: [Description]

### Testing Strategy
- Unit tests
- Integration tests
- Acceptance criteria

### Rollback Plan
- Contingency steps if issues arise

Best Practices

Keep prompts focused: One PRP per distinct problem
Be specific in plans: Each step should be actionable and measurable
Track progress: Use checkboxes to mark completed steps
Document assumptions: Make implicit knowledge explicit
Include validation: Define how success will be measured

File Naming Convention

prp-[description]-[timestamp].md

Example: prp-refactor-auth-module-2025-11-21.md

Integration with Agents

This structure works seamlessly with:

context-engineering-prp-generator agent (generates PRPs)
context-engineering-executor agent (executes plans)
context-engineering-orchestrator agent (coordinates workflows)