prompt-optimizer

SKILL.md

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:

Check if a CLAUDE.md exists in the working directory — read it for project conventions

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

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:

Research → Plan → Implement (TDD) → Review → Verify → Commit

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 4.6
Fast, cost-efficient for simple tasks

MEDIUM
Sonnet 4.6
Best coding model for standard work

HIGH
Sonnet 4.6 (main) + Opus 4.6 (planning)
Opus for architecture, Sonnet for implementation

EPIC
Opus 4.6 (blueprint) + Sonnet 4.6 (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 4.6
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:

帮我写一个用户登录页面

Phase 0 detects: package.json with Next.js 15, TypeScript, Tailwind CSS

Optimized Prompt (Full):

使用项目现有技术栈（Next.js 15 + TypeScript + Tailwind CSS）实现用户登录页面。

技术要求：
- 沿用项目现有的组件结构和路由约定
- 表单验证使用项目中已有的验证方案（检查是否已用 Zod/Yup/其他）
- 认证方式：沿用项目现有认证方案（如无，默认 JWT）
- 包含：邮箱/密码登录表单、表单验证、错误提示、加载状态、响应式布局

工作流：
1. /plan 先规划组件结构和认证流程，参考现有页面的模式
2. /tdd 测试先行：编写登录表单的单元测试和认证流程的集成测试
3. 实现登录页面和认证逻辑
4. /code-review 审查实现
5. /verify 验证所有测试通过且页面正常渲染

安全要求：
- 密码不明文传输
- 防止暴力破解（rate limiting）
- XSS 防护
- CSRF token

验收标准：
- 所有测试通过，覆盖率 80%+
- 页面在移动端和桌面端正常渲染
- 登录成功跳转到 dashboard，失败显示错误信息

不要做：
- 不要实现注册页面
- 不要实现忘记密码功能
- 不要修改现有的路由结构

Example 2: Moderate English Prompt

User input:

Add a REST API endpoint for user profile updates with validation

Phase 0 detects: go.mod with Go 1.22, Chi router

Optimized Prompt (Full):

Add a REST API endpoint for user profile updates (PATCH /api/users/:id).

Tech stack: Go 1.22 + Chi router (detected from project)

Requirements:
- PATCH /api/users/:id — partial update of user profile
- Input validation for fields: name, email, avatar_url, bio
- Auth: require valid token, users can only update own profile
- Return 200 with updated user on success
- Return 400 with validation errors on invalid input
- Return 401/403 for auth failures
- Follow existing API patterns in the codebase

Workflow:
1. /plan the endpoint structure, middleware chain, and validation logic
2. /tdd — write table-driven tests for success, validation failure, auth failure, not-found
3. Implement following existing handler patterns
4. /go-review
5. /verify — run full test suite, confirm no regressions

Do not:
- Modify existing endpoints
- Change the database schema (use existing user table)
- Add new dependencies without checking existing ones first (use search-first skill)

Example 3: EPIC Project

User input:

Migrate our monolith to microservices

Optimized Prompt (Full):

Use the blueprint skill to plan: "Migrate monolith to microservices architecture"

Before executing, answer these questions in the blueprint:
1. Which domain boundaries exist in the current monolith?
2. Which service should be extracted first (lowest coupling)?
3. Communication pattern: REST APIs, gRPC, or event-driven (Kafka/RabbitMQ)?
4. Database strategy: shared DB initially or database-per-service from start?
5. Deployment target: Kubernetes, Docker Compose, or serverless?

The blueprint should produce phases like:
- Phase 1: Identify service boundaries and create domain map
- Phase 2: Set up infrastructure (API gateway, service mesh, CI/CD per service)
- Phase 3: Extract first service (strangler fig pattern)
- Phase 4: Verify with integration tests, then extract next service
- Phase N: Decommission monolith

Each phase = 1 PR, with /verify gates between phases.
Use /save-session between phases. Use /resume-session to continue.
Use git worktrees for parallel service extraction when dependencies allow.

Recommended: Opus 4.6 for blueprint planning, Sonnet 4.6 for phase execution.

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