By shinpr
Run blind A/B evaluations of prompts and Claude Code skills in isolated git worktrees to compare original vs optimized versions, grade skill quality, and store improvement patterns from BP-001~008
Collects user feedback on comparison results and optimizes the knowledge base. Use when user indicates comparison results did not meet expectations or provides feedback on optimization quality. Adjusts confidence scores and manages knowledge entries.
Analyzes prompts against BP-001 through BP-008 and returns the prompt-optimization skill's gated JSON result. Use when prompt text or a prompt file is provided for optimization.
Executes a prompt in an isolated worktree environment and captures results. Use when worktree path and prompt are provided for execution. Returns execution status, outputs, and observations with strictly factual reporting only.
Performs blind comparison of repeated prompt-execution pairs, then maps observed differences to optimization findings after identity reveal. Use when original and optimized prompt trials are available.
Generates or modifies optimized skill files. In creation mode, builds from raw user knowledge. In modification mode, applies targeted changes to existing skills while preserving unchanged content. Use when creating new skills or updating existing ones.
Project-specific prompt optimization knowledge management. Use when storing or retrieving learned patterns from comparisons. Provides schema, extraction criteria, capacity management, and retention scoring.
Analyzes and optimizes prompts using BP-001~008 patterns and a gated 3-step flow. Use when "optimize this prompt", "review prompt quality", "analyze prompt issues", or creating/reviewing rashomon skill content.
Compares original and optimized prompts through repeated blind paired execution in git worktrees. Use when evaluating prompt improvement effects or learning prompt engineering through concrete examples.
Creates or updates Claude Code skills through interactive dialog, then evaluates effectiveness with sequential paired comparisons. Use when creating new skills, updating existing skills, or evaluating skill quality.
Git worktree management for isolated parallel prompt execution. Use when creating isolated environments for prompt comparison or managing worktree lifecycle. Provides creation, cleanup, and orphan detection scripts.
Uses power tools
Uses Bash, Write, or Edit tools
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Know whether your skills actually improve agent behavior — not just look different.
Inspired by the Rashomon effect — the idea that the same event can produce different outcomes depending on perspective. rashomon makes those differences explicit and comparable.
rashomon evaluates skills and prompts through blind comparison — running tasks with and without your changes in isolated environments, then comparing real outputs without knowing which version produced which.
rashomon is designed for:
Not ideal if:
/recipe-eval-skill create
Creates a skill through interactive dialog, then evaluates effectiveness:
What the evaluation report looks like:
Skill Quality: Grade A
- Project-specific rules clearly encoded, no critical issues
Trigger Check: pass (loaded through the Skill tool or its SKILL.md file)
Execution Effectiveness:
- Winner: with-skill
- Assessment: repeatable structural improvement across valid pairs
- Key difference: Retry constraints and three-stage catch ordering were applied
consistently (linked to skill Rules 3 and 6)
Recommendation: ship
/recipe-eval-skill api-error-handling skill's scope needs adjustment
Updates an existing skill, then evaluates old vs new version side by side.
See a real-world example: I Built a Skill Reviewer. Then I Ran It on Itself.
/recipe-eval-prompt Write a function to sort an array
Analyzes prompt issues, generates an improved version, and runs the original and optimized prompts in up to three blind, paired trials. The report highlights differences that recur across trials.
1. Analysis
- BP-002 (already satisfied): No consumer requirement selects a language,
ordering, or error policy, so those choices remain flexible.
2. Final Prompt
Write a function to sort an array
Result: Original sufficient - Rashomon stops before paired execution because no outcome-relevant ambiguity was found.
Requires Claude Code (this is a Claude Code plugin)
# 1. Start Claude Code
claude
# 2. Install the marketplace
/plugin marketplace add shinpr/rashomon
# 3. Install plugin
/plugin install rashomon@rashomon
# 4. Restart session (required)
# Exit and restart Claude Code
/recipe-eval-skill create
Create a new skill and evaluate its effectiveness.
/recipe-eval-skill my-skill-name what to change
Update an existing skill and compare old vs new.
/recipe-eval-prompt Your prompt here
From a file:
/recipe-eval-prompt Generate code following this skill: ./prompts/my-skill.md
For complex tasks that need more time, just mention it in natural language:
/recipe-eval-prompt Refactor the entire authentication module. This might take a while.
Skill Evaluation (/recipe-eval-skill)
├── skill-creator (generates/modifies skills)
├── skill-reviewer (grades quality A/B/C)
├── eval-executor (up to 3 valid pairs, sequential within each pair)
└── skill-eval-reporter (blind A/B comparison)
Prompt Evaluation (/recipe-eval-prompt)
├── prompt-analyzer (analyzes and optimizes)
├── prompt-executor (up to 3 valid pairs, parallel within each pair)
└── report-generator (compares results)
npx claudepluginhub shinpr/rashomon --plugin rashomonSkills + Subagents for backend development - Use skills for coding guidance, or run recipe workflows for full orchestrated agentic coding with specialized agents
Lightweight skills for users with existing workflows - coding best practices, testing principles, and design guidelines without recipe workflows or agents
Skills + Subagents for React/TypeScript - Use skills for coding guidance, or run recipe workflows for full orchestrated agentic coding with specialized agents
Skills + Subagents for fullstack development (backend + React/TypeScript) - Use skills for coding guidance, or run recipe workflows for full orchestrated agentic coding with specialized agents
Professional development workflows for Claude Code - Language-agnostic best practices, specialized agents, and quality assurance patterns for building production-ready software
Benchmark, evaluate, and optimize skills to ensure reliable performance across all LLMs
Self-evolving skill engine for Claude Code. Creates, scores, repairs, and hardens skills autonomously through recursive improvement cycles.
Create, edit, evaluate, and package Claude Code agent skills — full draft→test→review→improve lifecycle.
建立新技能、修改和改進現有技能、衡量技能效能。用於從零開始建立技能、編輯或優化現有技能、執行評估測試、基準測試效能分析、或優化技能描述以提升觸發準確度
4 persona Agent Team skill builder — spawn real agents to analyze and debate, then build working skills with auto eval/benchmark, description optimization via run_loop, and .skill packaging
Quality-gated skill authoring: create, recap, update, judge, and step-through-apply skills with HITL and an audit/feedback layer.