prompt-optimizer

name	prompt-optimizer
description	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", "rewrite this prompt", or explicitly asks to enhance prompt quality. Also triggers on Chinese equivalents: "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令". Specially handles short Chinese bug reports (the dominant real-world use case): runs Bug Report Triage to extract repro/expected/actual/environment, asks up to 3 clarifying questions if ≤ 2 fields are present, and inserts systematic-debugging as a hard prerequisite before any code change. DO NOT TRIGGER when: user wants the task executed directly, or says "just do it" / "直接做". DO NOT TRIGGER when user says "优化代码", "优化性能", "optimize performance", "optimize this code" — those are refactoring/performance tasks, not prompt optimization (unless the user explicitly invokes /prompt-optimize, in which case treat them as Bug Fix + Refactor combined).
origin	community
metadata	{"author":"YannJY02","version":"1.3.0","changelog":"1.3.0 — Phase 0.7 Project Context Probe. The skill now reads the actual\n repo (stack manifest, git state, README/CLAUDE.md/AGENTS.md)\n before producing the optimized prompt, so recommendations cite\n real file paths, branch names, and declared versions instead of\n generic templates. Hard rules R1-R6.5 prevent the probe from\n misleading downstream agents:\n • R1 — 3-section Facts / Inferences (UNVERIFIED) / Unknown block\n • R2 — never reference code symbols the probe did not actually Read\n (commit subjects and branch names are not code verification)\n • R3 — branch names do not determine intent; skill selection uses\n user prompt + Facts.stack only\n • R4 — declared manifest version ≠ installed version; lockfile\n must be checked when exact runtime version matters\n • R5 — README/CLAUDE.md/AGENTS.md content gets 1 line + source +\n last-modified date; declared-vs-detected conflicts get\n an explicit ⚠️ flag\n • R6 — mandatory \"Re-verify before mutating\" footer in every block\n • R6.5 — probe failures are explicit (\"PROBE FAILED: <reason>\"),\n never silently empty\n Section 3 (Optimized Prompt — Full) now MUST start with the verbatim\n Context Block and cite ≥ 2 Facts. Self-check gate added before\n publishing output. New Example 5 demonstrates the full probe →\n 3-section block → safe \"starting points to verify\" output pattern\n on a real SwiftUI iOS scenario. Budget: ≤ 6 read-only tool calls.\n Graceful degradation: works in non-git dirs, unknown stacks, and\n repos without self-description docs.\n1.2.1 — Fix phantom `/tdd` references (13 occurrences across Phase 1.5\n template, Phase 3 By-Intent table, Section 4 Quick Patterns,\n and all four examples). No `tdd` skill or command actually\n exists; the canonical name is `test-driven-development`\n (superpowers) — already mapped in the Phase 0.5 alias table\n but not applied to our own templates. This release closes that\n self-inconsistency. Added explicit `/tdd → /test-driven-development`\n row in the alias table to prevent regression.\n1.2.0 — Skill Existence & Alias Resolution (Phase 0.5) so we stop\n recommending phantom skills (`tdd-workflow`, `search-first`,\n `blueprint`, `tdd-guide` agent, etc. that don't exist on most\n installs). Multi-Intent Detection in Phase 1 with structured\n patterns and scope-bump rule. Conductor scope-gating column\n in Phase 2 (TRIVIAL/LOW skip, MEDIUM optional, HIGH default,\n EPIC required) — prevents over-ceremonialized small tasks.\n Best-Practices Skill Chains subsection in Phase 3 documenting\n the superpowers pipeline per intent (New Feature, Bug Fix,\n Performance, Research-then-Build, Multi-Intent, Refactor).\n1.1.0 — Added Bug Report Triage (Phase 1.5), Compact Mode (Phase 6),\n Tauri/Electron tech stacks, Research-then-Build intent,\n Performance intent, conductor/systematic-debugging/trace/analyze\n in component matching, real-data Chinese bug example.\n Driven by 8 real /prompt-optimize invocations: 7/8 were Chinese\n bug reports, 1/8 was research-then-build.\n1.0.0 — Initial release.\n"}

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
   • src-tauri/ + Cargo.toml + package.json → Tauri (Rust core + Web frontend)
   • electron.json / electron-builder.json / electron in package.json deps → Electron
   • expo.json / app.json with Expo SDK → React Native (Expo)
   • build.gradle / pom.xml → Java / Kotlin / Spring Boot
   • Package.swift → Swift
   • Gemfile → Ruby
   • composer.json → PHP
   • *.csproj / *.sln → .NET
   • Makefile / CMakeLists.txt → C / C++
   • cpanfile / Makefile.PL → Perl
3. Git context auto-pull — if the user's prompt mentions 当前分支 / current branch / this PR / 本次改动, run these read-only commands and inject results into Phase 4 context:
   • git status --short (uncommitted changes)
   • git log -5 --oneline (recent commits)
   • git diff --stat HEAD~1 (latest commit's surface area) This converts vague references into concrete file lists.
4. 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 0.5: Skill Existence & Alias Resolution

The component tables below were authored against a generic ECC distribution. Many users run OMC, superpowers, or their own custom installs where the same capability lives under a different skill name. Recommending a phantom skill wastes the user's time.

Preferred check (live index): before listing a skill in Section 2 / Section 3, read the auto-generated catalog:

cat ~/.claude/skills/_index.md

This file is regenerated by omc-manage setup (or manually via omc-manage skill index) and contains one row per installed skill with its name | description. Grep it for keywords from the user's intent:

grep -i "test\|tdd\|verification" ~/.claude/skills/_index.md

If a recommended skill does not appear in _index.md, replace it with a matching installed skill or fall back to the alias table below.

Fallback rule (when index is missing or empty): mentally check "Is this skill likely installed locally?" If unsure, follow the alias table or add a verification note.

Common alias map (generic ECC name → likely real names):

Generic ECC name	superpowers / OMC actual	Verification
tdd-workflow (skill)	test-driven-development (superpowers) OR tdd-generator (OMC)	ls ~/.claude/skills/test-driven-development
/tdd (slash) — no such command/skill	/test-driven-development (slash-invokes the superpowers skill)	ls ~/.claude/skills/test-driven-development
verification-loop (skill)	verification-before-completion (superpowers) OR verification-loop (OMC)	both common
search-first (skill)	external-context OR iterative-retrieval	check both
blueprint (skill)	conductor (preferred multi-session driver)	ls ~/.claude/skills/conductor
e2e-testing (skill)	e2e	—
tdd-guide (agent)	test-engineer (OMC)	—
build-error-resolver (agent)	debugger (OMC)	—
refactor-cleaner (agent)	code-simplifier (OMC)	—
doc-updater (agent)	writer (OMC)	—
python-reviewer / go-reviewer / etc.	usually just code-reviewer	—

Tech-stack-specific patterns (django-patterns, springboot-patterns, frontend-patterns, etc., listed in the By Tech Stack table) are aspirational on most installs — assume absent unless the user confirms otherwise. When referencing them in Section 3, write:

If you don't have <skill-name> installed, recommend the universal coding-standards skill instead, or use the conventions in the project's CLAUDE.md.

Discovery shortcut for the user: if _index.md is missing entirely, suggest they run omc-manage skill index --scope user (or just omc-manage setup, which regenerates it as a side effect). For a quality audit, use /oh-my-claudecode:skill-stocktake.

Phase 0.7: Project Context Probe (cheap, deterministic)

Goal: Ground the optimized prompt in what is actually true in this repo right now, not in generic templates. Without this phase, the skill produces plausible-sounding prompts that may reference nonexistent files, wrong versions, or off-stack tooling — the user's actual complaint.

Budget: ≤ 6 read-only tool calls. Each step is independent — failures degrade gracefully (see R6.5), never abort the whole phase.

5 probe actions, in order:

#	Action	Tool & Command	Output field
1	Confirm git repo	Bash: git rev-parse --is-inside-work-tree 2>/dev/null	is_git_repo: true/false
2	Scan stack manifests at repo root	One Glob with combined pattern: {package.json,Package.swift,Cargo.toml,go.mod,pyproject.toml,requirements.txt,*.csproj,Gemfile,pubspec.yaml,pom.xml,build.gradle*,mix.exs,composer.json}	manifests: [paths]
3	Read top manifest	Read first 50 lines of highest-priority match	stack: <name + declared version>, stack_source: <manifest>:<line>
4	Git current state (one call)	Bash: git rev-parse --abbrev-ref HEAD && echo --- && git status --short && echo --- && git log -3 --oneline && echo --- && git diff --stat HEAD~1 2>/dev/null | head -10	branch, uncommitted, recent_commits (subjects only), recent_diff_stat
5	Project self-description	Glob {CLAUDE.md,AGENTS.md,README.md} at repo root; Read first 30 lines of highest-priority match (priority: CLAUDE.md > AGENTS.md > README.md)	intent_source, intent_text (first non-empty heading + first ~3 prose lines), intent_last_modified

Graceful degradation:

• Action 1 = false → skip action 4. Mark Repo, branch, uncommitted, recent_commits as not in a git repo. Continue actions 2, 3, 5.
• Action 2 returns [] → stack: unknown — language-agnostic recommendations apply.
• Action 5 finds none → intent: no self-description found at repo root.
• Any single step throws → mark only that field PROBE FAILED: <one-line reason> (R6.5). Continue.

Output: Project Context Block (3-section structure, ALWAYS produced)

The probe always emits this block, even when most fields are UNKNOWN. It is appended to the top of Section 3: Optimized Prompt (see Output Format) and must remain verbatim — no paraphrasing, no summarization.

## 🔍 Project Context (probed YYYY-MM-DD HH:MM — starting point, NOT ground truth)

### Facts (directly observed in probe)
- Stack: <name + declared version>  ← from `<manifest>:<line>` (declared, installed version not verified)
- Repo: <basename of cwd> @ branch `<branch>` (<N commits ahead of <base>, or "no upstream tracking">)
- Uncommitted: <M/A/D files, or "clean working tree">
- Recent commit subjects (commit messages only — NOT code verification):
  - `<hash>` "<subject>"
  - `<hash>` "<subject>"
- Recent diff scope (`git diff --stat HEAD~1`): <file>: +N -M (or "no diff since HEAD~1")
- Project self-description (`<source-file>:<line>`, last modified <date>): "<first non-empty heading + opening line>"

### Inferences (UNVERIFIED — confirm before acting)
- <e.g., "Likely SwiftUI iOS work based on Package.swift + branch name">
- <e.g., "Stack manifest declares X but no lockfile read — installed version may differ">

### Unknown / Not Probed
- Whether <symbol mentioned in commit subjects> actually exists in source — Read source before referencing it as if it does
- Runtime/installed versions (only declared manifest was read)
- Whether project self-description still matches current architecture (last modified <date>)

⚠️ Re-verify before mutating: run `git status`, `Read` actual files. This block
   is probe-time context, not authoritative. If observation contradicts this
   block, trust observation and ignore this block.

6 anti-misleading hard rules (binding on Phase 3 / Phase 4 outputs):

These rules prevent the probe from producing context that downstream agents treat as truth when it is in fact inference, name-based guessing, or stale data. Violation = regenerate the optimized prompt.

ID	Rule	Why
R1	Block MUST be 3-section: ### Facts / ### Inferences (UNVERIFIED) / ### Unknown / Not Probed. Never mix categories. A fact mis-labeled as fact-but-actually-inferred is the primary misleading vector.	Forces explicit epistemic status on every line.
R2	Do not reference code symbols the probe did not actually read. A symbol seen only in a commit subject or branch name is NOT verified to exist. It may appear in Inferences or Unknown, never as an imperative ("extend AuthService").	A commit titled "add AuthService stub" does not prove AuthService exists, is complete, or is at the path one might guess.
R3	Branch names do not determine intent. A branch named feat/auth is a weak signal at best; it goes only in Inferences. Phase 3 skill selection is driven only by user prompt + Facts.stack.	Branch names are user-authored labels with no semantic guarantee.
R4	Manifest version ≠ installed version. All version facts must be marked declared in <manifest>, installed not verified. Tasks that need exact runtime version must explicitly check lockfile (package-lock.json, Cargo.lock, Package.resolved, poetry.lock, etc.).	package.json says React 18, node_modules may have 17.
R5	README / CLAUDE.md / AGENTS.md content gets 1 line + source + last-modified date. If declared description contradicts detected stack, append ⚠️ Conflict: declared "<X>" but stack indicates <Y> — verify with user.	Self-description docs drift; stack manifests do not.
R6	Banner footer is mandatory. The ⚠️ Re-verify before mutating line MUST appear verbatim at the bottom of every Context Block.	Drives downstream agent to treat block as starting context, not ground truth.
R6.5	Probe failures are explicit, never silently empty. Any failed action writes PROBE FAILED: <reason> for that field. Downstream agents seeing PROBE FAILED know to re-probe themselves; they would misread an empty field as "no problem".	An empty uncommitted field looks like a clean working tree.

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, 增加	"Build a login page"
Bug Fix	fix, broken, not working, error, 修复, 报错, 偶现, 不工作, 失效, 卡顿, 我发现一个问题, 你先看看	"Fix the auth flow" / "我发现头像不显示"
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"
Research-then-Build	"先调研 X 再实现", "参考 X 怎么做", "look at how X does it then build"	"先调研 Gemini CLI 自动补全再实现"
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"
Performance	"优化性能", "卡顿", "slow", "latency", "做性能优化"	"Windows 上卡顿"

Multi-intent prompts (detect at this phase, plan in Phase 2):

Many real prompts pack ≥ 2 intents into one sentence. Detect by counting distinct verbs/categories. Common patterns:

Pattern	Example	Intents
"先 X 再 Y"	"先做性能优化，再做 UX 优化"	Performance → Refactor
"X 同时 Y"	"修复 bug 同时加一个新页面"	Bug Fix + New Feature
"顺便/也"	"改这个 bug，顺便补测试"	Bug Fix + Testing
"调研 X 然后实现"	"调研 Gemini CLI 自动补全再实现"	Research-then-Build
"重构 X 顺便加 Y"	"重构 API 顺便补文档"	Refactor + Documentation

When ≥ 2 distinct intents detected:

1. Do not collapse into a single prompt. That produces ambiguous task ordering and loses scope discipline.
2. Bump scope assessment by one level (e.g., MEDIUM → HIGH). Multi-intent work has higher coordination cost than single-intent.
3. Recommend the conductor skill if combined scope is HIGH or above — each intent becomes a track:

   .omc/conductor/<feature-name>/
   ├── tracks/
   │   ├── perf-optimization/      # spec → plan → review
   │   └── ux-improvement/         # spec → plan → review
   

4. Order matters: explicit "先 X 再 Y" is sequential; "X + Y" with no ordering signal — recommend a default order based on dependency (e.g., investigation before fix, fix before refactor, refactor before docs).
5. Stop conditions per intent: each track gets its own /verify gate; do NOT proceed to track 2 until track 1's verify passes.

Note on Performance intent: The skill's "Do Not Use When" rule blocks 优化性能 as a trigger — but if the user explicitly invoked /prompt-optimize with a performance task, treat it like Bug Fix + Refactor combined: investigate first (analyze/trace), then refactor with measurement gates.

Phase 1.5: Bug Report Triage (only if Intent = Bug Fix or Performance)

Bug reports are the highest-volume use case for this skill, and they fail in predictable ways: vague repro, missing environment, no expected/actual. For Bug Fix and Performance intents, you MUST score the prompt against this checklist before generating the optimized prompt.

Field	What to extract	Default if missing
Repro steps	Concrete numbered steps to trigger the bug	Mark TODO: 用户补充复现步骤
Expected behavior	What should happen	Infer from prompt or mark TODO
Actual behavior	What does happen (error message, screenshot, log)	Mark TODO
Environment	OS (macOS/Windows/Linux), version, browser, device	Ask if absent and prompt mentions cross-platform symptoms
Reproducibility	100% / 偶现 (intermittent) / "first time"	Default 100% if not stated
Recent changes	Branch name, recent commits, suspected commit	Auto-fill via git log -5 (Phase 0)
Logs / stack trace	Error text, console output, network response	Mark TODO: 粘贴完整错误日志/截图

Scoring rule:

• ≥ 5 fields present → proceed to Phase 2 directly
• 3–4 fields present → fill TODO markers in optimized prompt; do NOT block
• ≤ 2 fields present → ask the user up to 3 clarifying questions BEFORE generating prompt. Prioritize: (1) repro, (2) environment if "偶现"/"intermittent"/cross-platform mentioned, (3) actual error/log

Special signals:

• "偶现" / "intermittent" / "flaky" / "sometimes" / "occasionally" → MUST ask: trigger pattern, frequency, environment differences
• "X 平台正常 Y 平台不正常" / "works on mac, broken on windows" → cross-platform Bug; recommend electron-driver skill if Electron, recommend platform-conditional repro
• "重启后/restart" → state-persistence bug; recommend reading any storage layer (localStorage, electron-store, Tauri store, sqlite) before fixing
• "性能/slow/卡顿" → Performance intent; recommend analyze skill + measurement-first workflow (record baseline, then optimize)

Bug Fix optimized-prompt template (used in Section 3 when intent = Bug Fix):

## 问题描述
[symptom in 1-2 sentences]

## 复现步骤
1. ...
2. ...
3. ...

## 期望 vs 实际
- 期望：...
- 实际：...

## 环境
- OS / 版本：[macOS 14 / Windows 11 / ...]
- 复现率：[100% / 偶现 N 次/M 次]
- 当前分支：[auto-filled via git]
- 相关日志：[paste here / TODO]

## 工作流
1. **不要直接改代码**。先用 systematic-debugging skill 定位根因
   - 列出至少 3 个候选假设
   - 对每个假设设计最小验证（添加日志 / 阅读相关代码）
2. /test-driven-development 写一个 failing 测试复现 bug（如果是 UI bug，写 e2e 用例）
3. 修复到 green
4. /verify 跨平台验证（如适用，跑 macOS + Windows）
5. /code-review

## 不要做
- 不要重构相邻无关代码
- 不要修改无关文件
- 不要在没有定位根因前提交"试试看"的修复

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	Conductor recommendation
TRIVIAL	Single file, < 50 lines	Direct execution	Skip — overkill
LOW	Single component or module	Single command or skill	Skip — single skill is enough
MEDIUM	Multiple components, same domain	Command chain + /verify	Optional — offer it but don't force; user choice
HIGH	Cross-domain, 5+ files	/plan first, then phased execution	Default ON — conductor track keeps phases coherent across reviews
EPIC	Multi-session, multi-PR, architectural shift	conductor (or blueprint) for multi-session plan	Required — single-session execution will lose context

Why the gating matters: Recommending conductor for a TRIVIAL task ("rename this variable") creates .omc/conductor/<track>/spec.md etc. — pure ceremony overhead. Conductor's value (durable spec/plan/review across sessions) only pays off when the task itself is durable (HIGH+).

Multi-intent override: per Phase 1, multi-intent prompts bump scope by one level. So a MEDIUM task with 2 intents → HIGH → conductor defaults ON.

Phase 3: ECC Component Matching

Map intent + scope + Phase 0.7 Facts.stack to specific ECC components.

HARD RULE (binding): Component selection MUST be driven by Project Context Block → Facts → Stack when present. When matching the By-Tech-Stack table below, skip rows that do not match the detected stack — never list React skills for a Swift project, never list Django skills for a Go project. Inferences and Unknown fields are advisory only — they MAY surface a "verify this assumption" note, but MUST NOT drive skill selection.

If Facts.stack is unknown (no manifest detected), fall back to the language-agnostic intent-only recommendations and explicitly say so in Section 5 rationale: "Stack unknown — recommendations are generic; user should re-run after declaring stack."

By Intent Type

Intent	Commands	Skills	Agents
New Feature	/plan, /test-driven-development, /code-review, /verify	tdd-workflow, verification-loop	planner, tdd-guide, code-reviewer
Bug Fix	/test-driven-development, /verify	systematic-debugging (REQUIRED first), trace, analyze, debug, verification-loop	debugger, tdd-guide, code-reviewer
Bug Fix (intermittent / 偶现)	/verify	systematic-debugging, trace, e2e (for flaky reproduction harness)	debugger, tracer
Bug Fix (cross-platform)	/verify	systematic-debugging, electron-driver (if Electron)	debugger, code-reviewer
Performance	/verify	analyze, trace, verification-loop	architect, code-reviewer
Refactor	/refactor-clean, /code-review, /verify	verification-loop	refactor-cleaner, code-reviewer
Research	/plan	search-first, iterative-retrieval, external-context	—
Research-then-Build	/plan	external-context (research) → conductor (track delivery) → /test-driven-development per phase	planner → executor
Testing	/test-driven-development, /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, writer
Infrastructure	/plan, /verify	docker-patterns, deployment-patterns, database-migrations	architect
Design (MEDIUM-HIGH)	/plan	—	planner, architect
Design (EPIC)	—	conductor (multi-session track) OR blueprint	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	code-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
Tauri (Rust + Web)	rust-patterns, frontend-patterns, coding-standards (note IPC bridge between Rust core and Web)	code-reviewer
Electron	electron-driver (E2E), frontend-patterns, coding-standards (note main vs renderer process)	code-reviewer
React Native / Expo	frontend-patterns, coding-standards	code-reviewer
Cross-platform desktop bug	electron-driver (if Electron) + systematic-debugging + platform-conditional repro	debugger
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

Best-Practices Skill Chains

The two tables above pick single skills; this subsection wires them into ordered chains that match documented community best practices (primarily the superpowers pipeline). Use these chains in Section 3 — don't just dump a flat list of skills.

Chain notation: A → B → C means run A first, then B, then C, with each step gated by its own success criterion. [X] = optional, include only if scope/risk warrants it.

Chain: New Feature (HIGH+ scope)

brainstorming                       (clarify intent + requirements)
  → using-git-worktrees             (isolate work)
  → conductor (init track)          (create spec.md / plan.md skeleton)
    → writing-plans                 (fill plan.md with concrete steps)
    → [research] external-context   (only if novel domain)
    → test-driven-development       (red → green per step)
    → verification-before-completion (evidence-based check)
    → requesting-code-review        (independent review pass)
  → finishing-a-development-branch  (merge / PR / cleanup)

Chain: New Feature (LOW–MEDIUM scope, no conductor)

brainstorming
  → writing-plans                   (lightweight inline plan)
  → test-driven-development
  → verification-before-completion
  → [requesting-code-review]        (skip for trivial)

Chain: Bug Fix (any scope)

systematic-debugging                (REQUIRED: hypotheses → evidence)
  → [trace]                         (only if intermittent / 偶现)
  → test-driven-development         (failing test reproduces bug)
  → verification-before-completion  (test passes + no regressions)
  → [requesting-code-review]        (for non-trivial fixes)
  → finishing-a-development-branch

Chain: Performance Optimization

analyze                             (baseline measurement: profile / timing)
  → trace                           (locate hotspot with evidence)
  → writing-plans                   (which optimizations, in what order)
  → test-driven-development         (regression test for behavior)
  → [implement]                     (one optimization at a time)
  → verification-before-completion  (re-measure: did it actually improve?)
  → finishing-a-development-branch

Chain: Research-then-Build

external-context                    (study reference implementation)
  → produce comparison report       (what to copy, what to skip, what to adapt)
  → brainstorming                   (apply learnings to our context)
  → conductor (init multi-phase track)
    → phase-1: minimal viable port
    → phase-2: project-specific adaptations
    → phase-3: integration + tests
  → finishing-a-development-branch

Chain: Multi-Intent Prompt

brainstorming                       (decompose into intents, prioritize)
  → conductor (multi-track init)    (one track per intent)
    → for each track in dependency order:
        → use the appropriate single-intent chain above
        → /verify gate before next track starts
  → finishing-a-development-branch  (one PR or split per track, user's call)

Chain: Refactor (no behavior change)

[code-review of current state]      (understand existing intent)
  → writing-plans                   (refactor steps, each behavior-preserving)
  → test-driven-development         (characterization tests if absent)
  → ai-slop-cleaner                 (only if cleaning AI-generated bloat)
  → verification-before-completion  (behavior unchanged: tests still pass)
  → finishing-a-development-branch

When to deviate from these chains:

• User explicitly says "skip TDD" → drop test-driven-development
• Project's CLAUDE.md mandates a different workflow → follow it (CLAUDE.md > skill chains, per superpowers using-superpowers priority rule)
• Time-boxed prototype / spike → can drop verification-before-completion + requesting-code-review (mark explicitly: "this is a spike, not production")

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
• For multi-session structured delivery, prefer the conductor skill (creates .omc/conductor/ tracks with Context → Spec → Plan → Implement artifacts that survive across sessions)

Phase 6: Compact Mode (output short-circuit)

When ALL of these are true, skip Section 1 (Diagnosis) and Section 5 (Rationale) in the output — just deliver Section 2 (Components) + Section 3 (Full prompt) + Section 4 (Quick) + Footer:

• Original prompt is < 300 characters AND
• Single, well-defined issue (no multi-part request) AND
• Tech stack auto-detected in Phase 0 AND
• Bug Triage scored ≥ 5/7 OR intent ≠ Bug Fix

Why: Real telemetry shows the majority of /prompt-optimize invocations are short Chinese bug reports. Forcing them through full diagnosis adds reading overhead with no signal. Diagnosis tables matter when prompts are ambiguous — not when they're already concrete.

If Compact Mode triggers, prefix Section 2 with: > Compact mode (short single-issue prompt). Full diagnosis skipped — ask if you want it.

---

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.

MANDATORY STRUCTURE (binding):

1. First, paste the Project Context Block from Phase 0.7 verbatim. Do not summarize, do not paraphrase. The downstream agent needs the same epistemic separation (Facts / Inferences / Unknown) the probe produced.
2. Then, a blank line.
3. Then, the task content, which MUST:
   • Cite at least 2 specific items from Facts by file path, branch name, manifest line, or commit hash. Generic language like "use the existing auth code" is a FAIL — replace with "Read Sources/Auth/LoginView.swift (uncommitted change, see Facts)".
   • Phrase next-step references as starting points to verify, NOT as imperatives. Good: "Read LoginView.swift first to see what's already there." Bad: "Extend LoginView.swift."
   • Never reference a code symbol that appeared only in Inferences or Unknown (R2 — see Phase 0.7). Such references must downgrade to "search Grep for X before assuming it exists."

Other required content:

• Clear task description (after Context Block)
• /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).

Self-check gate (run before publishing Section 3 output):

Check	If FAIL
Does Section 3 start with the verbatim Project Context Block?	Regenerate; prepend the block
Does the task content cite ≥ 2 items from Facts by name/path?	Regenerate; replace generic references with specific Facts
Does any imperative reference a symbol that only appeared in Inferences or Unknown?	Regenerate; downgrade to "verify before extending"
Is the ⚠️ Re-verify before mutating footer present in the block?	Regenerate; add the footer

Section 4: Optimized Prompt — Quick Version

A compact version for experienced ECC users. Vary by intent type:

Intent	Quick Pattern
New Feature	/plan [feature]. /test-driven-development to implement. /code-review. /verify.
Bug Fix	Use systematic-debugging for [bug] — list 3 hypotheses, verify each. Then /test-driven-development: write failing test, fix to green. /verify.
Bug Fix (intermittent)	Use trace skill for [intermittent bug] — competing hypotheses with evidence. Build flaky-repro harness in /e2e. Fix only after 100% repro. /verify.
Bug Fix (cross-platform)	Use systematic-debugging for [bug]. Repro on both [platform A] and [platform B]. Fix. /verify on both platforms.
Performance	Use analyze for [slow path] — measure baseline first (timing/profile). Identify top 3 hotspots. Fix one at a time, re-measure after each. /verify regression.
Refactor	/refactor-clean [scope]. /code-review. /verify.
Research	Use external-context skill for [topic]. /plan based on findings.
Research-then-Build	Use external-context to study [reference X]. Produce comparison report. Then use conductor skill to track delivery: spec → plan → /test-driven-development per phase.
Testing	/test-driven-development [module]. /e2e for critical flows. /test-coverage.
Review	/code-review. Then use security-reviewer agent.
Docs	/update-docs. /update-codemaps.
EPIC	Use conductor skill (or blueprint) 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.

For bug reports: before pasting the optimized prompt into a new session, attach any error logs, stack traces, or screenshots — they make the investigation 10× faster than text descriptions alone.

---

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. /test-driven-development 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. /test-driven-development — 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: Chinese Bug Report (real-data pattern)

User input:

当前分支的分享 html 项目或者 md 文档的功能，存在一个问题，就是如果用户修改已经分享的文件，无法再次分享，这样链接始终不会发生改变

Phase 0 detects: Tauri (Rust + Web) project. Git context: 3 uncommitted files in src/share/, branch feat/share-html.

Phase 1.5 Triage: repro 1/7 (only symptom), expected/actual implicit, environment unspecified, reproducibility 100% inferred. Score 3/7 → fill TODO markers, do not block.

Optimized Prompt (Full):

## 问题描述
分享 HTML 项目 / MD 文档功能：用户修改已分享文件后，无法再次生成新链接，
链接始终不更新。

## 复现步骤
1. 在当前分支（feat/share-html）打开任意 HTML 项目或 MD 文档
2. 点击分享，记录生成的链接 A
3. 修改文件内容并保存
4. 再次点击分享
5. 观察生成的链接是否变化

## 期望 vs 实际
- 期望：再次分享时生成新链接（或同链接但内容已更新）
- 实际：分享按钮无响应 / 链接不变 / 旧内容（请确认是哪种）

## 环境
- OS / 版本：[macOS / Windows，请补充]
- 复现率：100%（推测，请确认）
- 当前分支：feat/share-html
- 相关文件：src/share/*（git status 显示 3 个未提交改动 — 是否相关？）

## 工作流
1. **不要直接改代码**。先用 systematic-debugging skill 定位根因，候选假设：
   - H1: 分享缓存（按文件路径 key）未失效
   - H2: 文件 hash 计算逻辑用了 mtime 而非内容 hash
   - H3: 分享接口幂等性设计阻止了重复请求
   - H4: 前端短路 — 检测到"已分享"就不再触发请求
   对每个假设：阅读 src/share/ 相关代码 + 添加临时日志验证
2. /test-driven-development 写 e2e 测试用例：分享 → 修改 → 再分享，断言链接或内容变化
3. 修复到 green
4. /verify：跑 e2e 测试 + macOS + Windows 各手测一次（Tauri 项目跨平台）
5. /code-review

## 不要做
- 不要改其他分享类型（仅 HTML / MD 文档）
- 不要重构 share 模块的整体架构
- 不要在没定位根因前做"清缓存"之类的猜测性修复

Optimized Prompt (Quick):

Use systematic-debugging for "分享 HTML/MD 后修改文件链接不更新" — list 3 hypotheses
(cache key, hash strategy, idempotent API), verify each. /test-driven-development write failing e2e.
Fix to green. /verify on macOS + Windows.

Example 4: 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.

Example 5: Phase 0.7 — Project-Aware Recommendation (SwiftUI repo)

Demonstrates the v1.3.0 probe + 3-section Context Block + safe "starting points to verify" output. Note how the optimized prompt avoids referencing AuthService as if it exists (R2) and labels the branch signal as inference only (R3).

User input (vague Chinese):

帮我加个登录功能

Phase 0.7 probe output (5 tool calls):

• Action 1: git rev-parse --is-inside-work-tree → true
• Action 2: Glob finds Package.swift at repo root
• Action 3: Read Package.swift lines 1-50 → swift-tools-version: 6.0, platform iOS .v18
• Action 4: git combined → branch feat/auth (2 ahead of main), uncommitted M Sources/Auth/LoginView.swift, recent commits include a1b2c3 add AuthService stub, d4e5f6 wire keychain
• Action 5: CLAUDE.md exists, line 1 reads "# AcmeApp iOS companion (SwiftUI)"

Optimized Prompt (Full):

## 🔍 Project Context (probed 2026-05-27 14:30 — starting point, NOT ground truth)

### Facts (directly observed in probe)
- Stack: Swift 6.0 + SwiftUI, target iOS 18  ← from `Package.swift:5` (declared, installed toolchain not verified)
- Repo: AcmeApp @ branch `feat/auth` (2 commits ahead of `main`)
- Uncommitted: M `Sources/Auth/LoginView.swift`
- Recent commit subjects (commit messages only — NOT code verification):
  - `a1b2c3` "add AuthService stub"
  - `d4e5f6` "wire keychain"
  - `9f8e7d` "scaffold Auth module"
- Recent diff scope (`git diff --stat HEAD~1`): `Sources/Auth/LoginView.swift`: +45 -12
- Project self-description (`CLAUDE.md:1`, last modified 2026-04-30): "AcmeApp iOS companion (SwiftUI)"

### Inferences (UNVERIFIED — confirm before acting)
- Likely SwiftUI auth feature work in progress (branch name + recent commit subjects)
- A type named "AuthService" may exist (commit subject reference) — NOT verified by reading any file

### Unknown / Not Probed
- Whether `AuthService` actually exists as a Swift type — `Grep "AuthService" Sources/` before referencing
- Installed Swift toolchain version (only `Package.swift` declared version was read)
- Whether `LoginView.swift` is the intended host for login UI or just a scratch file

⚠️ Re-verify before mutating: run `git status`, `Read` actual files. This block
   is probe-time context, not authoritative. If observation contradicts this
   block, trust observation and ignore this block.

---

**Task**: Implement login functionality for AcmeApp.

**Required skills**: `swiftui-pro` (review/idiom), `test-driven-development` (write failing test first).

**Starting points to verify (NOT commands to obey blindly):**

1. `Sources/Auth/LoginView.swift` already has uncommitted changes (+45 -12 vs HEAD~1). **Read it first** to see what's already drafted before adding new code.
2. Commit log mentions "AuthService stub" — **before** importing or extending it, run `Grep "AuthService" Sources/` to confirm the type exists and is at a usable state. Treat the name as a lead, not a fact.
3. Branch is `feat/auth` with 2 commits ahead of `main` — verify this is the intended working branch. If unclear, ask the user.
4. `CLAUDE.md` declares SwiftUI iOS — use SwiftUI APIs (`@State`, `@Observable`, `NavigationStack`) and `iOS 18` features. Confirm by reading `Package.swift` platforms array before using iOS-26-only APIs.

**Workflow:**
1. `Read Sources/Auth/LoginView.swift` → understand existing scaffold.
2. `Grep` for `AuthService`, `Keychain` patterns → ground the implementation in what exists.
3. Use `test-driven-development`: write failing test for the login happy path first.
4. Implement minimum code to pass; let `swiftui-pro` review the View structure.
5. `/verify` — build, run tests, manually exercise the simulator flow.

**Acceptance criteria:**
- Login screen accepts email + password input, validates non-empty
- Successful auth navigates to main app screen
- Failed auth shows inline error
- Credentials persist via Keychain (extend existing wiring from `d4e5f6`, do NOT re-implement)
- Unit tests cover validation + success + failure paths

**Scope boundaries:**
- Do NOT redesign `AuthService` interface — extend it if it exists; flag for user if it doesn't
- Do NOT switch branch — work continues on `feat/auth`
- Do NOT introduce a new auth library (no Firebase / Auth0 / etc.) without asking

Why this output is safer than the v1.2.x style:

v1.2.x risk	v1.3.0 mitigation
Would have said "Use swiftui-pro to add login" without naming files	Cites LoginView.swift, Package.swift:5, branch feat/auth, commit d4e5f6 (R1, ≥ 2 Facts cited)
Might have written "extend AuthService" as imperative	Downgraded to "Grep AuthService first — treat the name as a lead, not a fact" (R2)
Would have inferred "auth feature" from branch name	Branch name in Inferences, intent confirmed via user prompt only (R3)
Would have said "Swift 6.0" as if it were installed	"declared, installed toolchain not verified" (R4)
Would have implied CLAUDE.md content was current truth	Cited with last-modified date (R5)
No instruction to re-verify	⚠️ Re-verify before mutating footer (R6)

---

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
external-context	Research external docs/products (e.g., "调研 Gemini CLI 怎么做的")
systematic-debugging	Always referenced for Bug Fix intent — root-cause before code
trace	Bug Fix with competing hypotheses, intermittent / 偶现 bugs
analyze	Performance intent or unknown-cause investigation
debug	OMC session/repo state diagnosis
conductor	Multi-session structured delivery (replaces blueprint for most cases)
blueprint	EPIC-scope when conductor is unavailable (legacy)
electron-driver	Electron cross-platform bugs requiring E2E repro
strategic-compact	Long session context management
cost-aware-llm-pipeline	Token optimization recommendations