Analyze raw prompts, identify intent and gaps, match ECC components (skills/commands/agents/hooks), and output a ready-to-paste optimized prompt. Advisory role only — never executes the task itself. TRIGGER when: user says "optimize prompt", "improve my prompt", "how to write a prompt for", "help me

Prompt Optimizer Analyze a draft prompt, critique it, match it to ECC ecosystem components, and output a complete optimized prompt the user can paste and run. When to Use User says "optimize this prompt", "improve my prompt", "rewrite this prompt" User says "help me write a better prompt for..." User says "what's the best way to ask Claude Code to..." User says "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令" User pastes a draft prompt and asks for feedback or enhancement User says "I don't know how to prompt for this" User says "how should I use ECC for..." User explicitly invokes /prompt optimize Do Not Use When User wants the task done directly (just execute it) User says "优化代码", "优化性能", "optimize this code", "optimize performance" — these are refactoring tasks, not prompt optimization User is asking about ECC configuration (use configure ecc instead) User wants a skill inventory (use skill stocktake instead) User says "just do it" or "直接做" How It Works Advisory only — do not execute the user's task. Do NOT write code, create files, run commands, or take any implementation action. Your ONLY output is an analysis plus an optimized prompt. If the user says "just do it", "直接做", or "don't optimize, just execute", do not switch into implementation mode inside this skill. Tell the user this skill only produces optimized prompts, and instruct them to make a normal task request if they want execution instead. Run this 6 phase pipeline sequentially. Present results using the Output Format below. Analysis Pipeline Phase 0: Project Detection Before analyzing the prompt, detect the current project context: 1. Check if a CLAUDE.md exists in the working directory — read it for project conventions 2. Detect tech stack from project files: package.json → Node.js / TypeScript / React / Next.js go.mod → Go pyproject.toml / requirements.txt → Python Cargo.toml → Rust build.gradle / pom.xml → Java / Kotlin (then check for quarkus in build file → Quarkus, or spring boot → Spring Boot) Package.swift → Swift Gemfile → Ruby composer.json → PHP .csproj / .sln → .NET Makefile / CMakeLists.txt → C / C++ cpanfile / Makefile.PL → Perl 3. Note detected tech stack for use in Phase 3 and Phase 4 If no project files are found (e.g., the prompt is abstract or for a new project), skip detection and flag "tech stack unknown" in Phase 4. Phase 1: Intent Detection Classify the user's task into one or more categories: Category Signal Words Example New Feature build, create, add, implement, 创建, 实现, 添加 "Build a login page" Bug Fix fix, broken, not working, error, 修复, 报错 "Fix the auth flow" Refactor refactor, clean up, restructure, 重构, 整理 "Refactor the API layer" Research how to, what is, explore, investigate, 怎么, 如何 "How to add SSO" Testing test, coverage, verify, 测试, 覆盖率 "Add tests for the cart" Review review, audit, check, 审查, 检查 "Review my PR" Documentation document, update docs, 文档 "Update the API docs" Infrastructure deploy, CI, docker, database, 部署, 数据库 "Set up CI/CD pipeline" Design design, architecture, plan, 设计, 架构 "Design the data model" Phase 2: Scope Assessment If Phase 0 detected a project, use codebase size as a signal. Otherwise, estimate from the prompt description alone and mark the estimate as uncertain. Scope Heuristic Orchestration TRIVIAL Single file, < 50 lines Direct execution LOW Single component or module Single command or skill MEDIUM Multiple components, same domain Command chain + /verify HIGH Cross domain, 5+ files /plan first, then phased execution EPIC Multi session, multi PR, architectural shift Use blueprint skill for multi session plan Phase 3: ECC Component Matching Map intent + scope + tech stack (from Phase 0) to specific ECC components. By Intent Type Intent Commands Skills Agents New Feature /plan, /tdd, /code review, /verify tdd workflow, verification loop planner, tdd guide, code reviewer Bug Fix /tdd, /build fix, /verify tdd workflow tdd guide, build error resolver Refactor /refactor clean, /code review, /verify verification loop refactor cleaner, code reviewer Research /plan search first, iterative retrieval — Testing /tdd, /e2e, /test coverage tdd workflow, e2e testing tdd guide, e2e runner Review /code review security review code reviewer, security reviewer Documentation /update docs, /update codemaps — doc updater Infrastructure /plan, /verify docker patterns, deployment patterns, database migrations architect Design (MEDIUM HIGH) /plan — planner, architect Design (EPIC) — blueprint (invoke as skill) planner, architect By Tech Stack Tech Stack Skills to Add Agent Python / Django django patterns, django tdd, django security, django verification, python patterns, python testing python reviewer Go golang patterns, golang testing go reviewer, go build resolver Spring Boot / Java springboot patterns, springboot tdd, springboot security, springboot verification, java coding standards, jpa patterns java reviewer Quarkus / Java quarkus patterns, quarkus tdd, quarkus security, quarkus verification, java coding standards, jpa patterns java reviewer Kotlin / Android kotlin coroutines flows, compose multiplatform patterns, android clean architecture kotlin reviewer TypeScript / React frontend patterns, backend patterns, coding standards code reviewer Swift / iOS swiftui patterns, swift concurrency 6 2, swift actor persistence, swift protocol di testing code reviewer PostgreSQL postgres patterns, database migrations database reviewer Perl perl patterns, perl testing, perl security code reviewer C++ cpp coding standards, cpp testing code reviewer Other / Unlisted coding standards (universal) code reviewer Phase 4: Missing Context Detection Scan the prompt for missing critical information. Check each item and mark whether Phase 0 auto detected it or the user must supply it: [ ] Tech stack — Detected in Phase 0, or must user specify? [ ] Target scope — Files, directories, or modules mentioned? [ ] Acceptance criteria — How to know the task is done? [ ] Error handling — Edge cases and failure modes addressed? [ ] Security requirements — Auth, input validation, secrets? [ ] Testing expectations — Unit, integration, E2E? [ ] Performance constraints — Load, latency, resource limits? [ ] UI/UX requirements — Design specs, responsive, a11y? (if frontend) [ ] Database changes — Schema, migrations, indexes? (if data layer) [ ] Existing patterns — Reference files or conventions to follow? [ ] Scope boundaries — What NOT to do? If 3+ critical items are missing , ask the user up to 3 clarification questions before generating the optimized prompt. Then incorporate the answers into the optimized prompt. Phase 5: Workflow & Model Recommendation Determine where this prompt sits in the development lifecycle: For MEDIUM+ tasks, always start with /plan. For EPIC tasks, use blueprint skill. Model recommendation (include in output): Scope Recommended Model Rationale TRIVIAL LOW Sonnet 5 Fast, cost efficient for simple tasks MEDIUM Sonnet 5 Best coding model for standard work HIGH Sonnet 5 (main) + Opus 5 (planning) Opus for architecture, Sonnet for implementation EPIC Opus 5 (blueprint) + Sonnet 5 (execution) Deep reasoning for multi session planning Multi prompt splitting (for HIGH/EPIC scope): For tasks that exceed a single session, split into sequential prompts: Prompt 1: Research + Plan (use search first skill, then /plan) Prompt 2 N: Implement one phase per prompt (each ends with /verify) Final Prompt: Integration test + /code review across all phases Use /save session and /resume session to preserve context between sessions Output Format Present your analysis in this exact structure. Respond in the same language as the user's input. Section 1: Prompt Diagnosis Strengths: List what the original prompt does well. Issues: Issue Impact Suggested Fix (problem) (consequence) (how to fix) Needs Clarification: Numbered list of questions the user should answer. If Phase 0 auto detected the answer, state it instead of asking. Section 2: Recommended ECC Components Type Component Purpose Command /plan Plan architecture before coding Skill tdd workflow TDD methodology guidance Agent code reviewer Post implementation review Model Sonnet 5 Recommended for this scope Section 3: Optimized Prompt — Full Version Present the complete optimized prompt inside a single fenced code block. The prompt must be self contained and ready to copy paste. Include: Clear task description with context Tech stack (detected or specified) /command invocations at the right workflow stages Acceptance criteria Verification steps Scope boundaries (what NOT to do) For items that reference blueprint, write: "Use the blueprint skill to..." (not /blueprint , since blueprint is a skill, not a command). Section 4: Optimized Prompt — Quick Version A compact version for experienced ECC users. Vary by intent type: Intent Quick Pattern New Feature /plan [feature]. /tdd to implement. /code review. /verify. Bug Fix /tdd — write failing test for [bug]. Fix to green. /verify. Refactor /refactor clean [scope]. /code review. /verify. Research Use search first skill for [topic]. /plan based on findings. Testing /tdd [module]. /e2e for critical flows. /test coverage. Review /code review. Then use security reviewer agent. Docs /update docs. /update codemaps. EPIC Use blueprint skill for "[objective]". Execute phases with /verify gates. Section 5: Enhancement Rationale Enhancement Reason (what was added) (why it matters) Footer Not what you need? Tell me what to adjust, or make a normal task request if you want execution instead of prompt optimization. Examples Trigger Examples "Optimize this prompt for ECC" "Rewrite this prompt so Claude Code uses the right commands" "帮我优化这个指令" "How should I prompt ECC for this task?" Example 1: Vague Chinese Prompt (Project Detected) User input: Phase 0 detects: package.json with Next.js 15, TypeScript, Tailwind CSS Optimized Prompt (Full): Example 2: Moderate English Prompt User input: Phase 0 detects: go.mod with Go 1.22, Chi router Optimized Prompt (Full): Example 3: EPIC Project User input: Optimized Prompt (Full): Related Components Component When to Reference configure ecc User hasn't set up ECC yet skill stocktake Audit which components are installed (use instead of hardcoded catalog) search first Research phase in optimized prompts blueprint EPIC scope optimized prompts (invoke as skill, not command) strategic compact Long session context management cost aware llm pipeline Token optimization recommendations

prompt-optimizer