harness-creator
Design and create AI-agent infrastructure for codebases: AGENTS.md, documentation architecture (docs/), linters with actionable errors (scripts/lint-*), harness/ configs, and CI integration. Creates files directly — never writes business/application code.
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
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name harness-creator description Design and create AI-agent infrastructure for codebases: AGENTS.md, documentation architecture (docs/), linters with actionable errors (scripts/lint-*), harness/ configs, and CI integration. Creates files directly — never writes business/application code. Harness Creator Design and create Harness Engineering infrastructure so AI agents can work reliably in a codebase. Core Philosophy : "Intelligence without infrastructure is just a demo." The Agent Harness is the Operating System — the LLM is just the CPU. The repository becomes the single source of truth — if an agent can't see it in context, it doesn't exist. Unified Workflow This skill follows a single unified workflow regardless of project state (empty, existing code, or existing harness). The core idea: detect the gap between current state and target state, then fill it . ┌─────────────────────────────────────────────────────────────────────┐ │ Phase 1: Quick Detection + Intent Confirmation │ │ (5 min) What exists? What does user want? │ └─────────────────────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Phase 2: Parallel Analysis (spawn subagents) │ │ - Code Architecture Agent: imports, layers, patterns │ │ - Harness State Agent: existing docs, linters, configs │ │ - Environment Agent: dependencies, services, secrets │ └─────────────────────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Phase 3: Delta Synthesis │ │ Merge analysis results → compute what needs to be created/updated │ └─────────────────────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Phase 4: Parallel Creation/Update (spawn subagents) │ │ - Documentation Agent: AGENTS.md, docs/* │ │ - Linter Agent: scripts/lint-* │ │ - Config Agent: harness/*, Makefile, CI │ └─────────────────────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Phase 5: Verification + Handoff │ │ Run linters, verify files, present summary │ └─────────────────────────────────────────────────────────────────────┘ Phase 1: Quick Detection + Intent Confirmation Goal : In under 5 minutes, understand project state and user intent. 1.1 Project State Detection Run this quick scan: # Count files file_count=$(find . - type f ! -path './.git/*' ! -path './node_modules/*' ! -path './vendor/*' 2>/dev/null | wc -l) code_files=$(find . - type f \( -name "*.go" -o -name "*.ts" -o -name "*.js" -o -name "*.py" -o -name "*.rs" \) ! -path './.git/*' ! -path './node_modules/*' ! -path './vendor/*' 2>/dev/null | wc -l) # Check harness components has_agents_md=$( test -f AGENTS.md && echo "yes" || echo "no" ) has_architecture=$( test -f docs/ARCHITECTURE.md && echo "yes" || echo "no" ) has_linters=$( ls scripts/lint-* 2>/dev/null | wc -l) has_harness_dir=$( test -d harness && echo "yes" || echo "no" ) has_makefile=$( test -f Makefile && echo "yes" || echo "no" ) # Detect tech stack if test -f go.mod; then TECH= "Go" elif test -f package.json; then TECH= "TypeScript/Node.js" elif test -f requirements.txt || test -f pyproject.toml; then TECH= "Python" else TECH= "Unknown" fi 1.2 Classify Project State Based on detection: State Criteria Action Empty file_count < 5 AND code_files = 0 Guide user through project choices first Code Only code_files > 0 AND has_agents_md = "no" Full analysis + full creation Partial Harness has_agents_md = "yes" AND (has_linters = 0 OR has_harness_dir = "no") Gap analysis + fill gaps Full Harness All components exist Audit + improvement suggestions 1.3 Intent Confirmation If AskUserQuestion is available , confirm scope: { "question" : "What's your priority for this harness setup?" , "header" : "Scope" , "multiSelect" : false , "options" : [ { "label" : "Full harness (Recommended)" , "description" : "Complete setup: AGENTS.md, docs, linters, eval framework, CI integration" } , { "label" : "Documentation only" , "description" : "Just AGENTS.md + docs/ for now, add linters/evals later" } , { "label" : "Minimal viable" , "description" : "Only AGENTS.md + basic lint-deps, can expand later" } ] } If Empty project , also ask for basics: { "question" : "What tech stack for this project?" , "header" : "Tech Stack" , "multiSelect" : false , "options" : [ { "label" : "Go" , "description" : "CLI tools, high-performance services, system programming" } , { "label" : "TypeScript/Node.js" , "description" : "Web APIs, full-stack apps, rapid prototyping" } , { "label" : "Python" , "description" : "Data processing, ML/AI, scripting" } ] } If AskUserQuestion is NOT available , use detected values and document assumptions: ## Auto-Detected Context | Field | Value | Confidence | Evidence | |-------|-------|------------|----------| | Tech Stack | {TECH} | High | Found {config file} | | Project State | {state} | High | {criteria matched} | | Scope | Full harness | Default | No user preference specified | Proceeding with these assumptions. Tell me if any need adjustment. Phase 2: Parallel Analysis Goal : Deeply understand codebase through parallel analysis agents. This speeds up the process significantly. 2.1 Spawn Analysis Agents Spawn these agents in a single message so they run in parallel: Agent("code-architecture-analysis", prompt=""" Analyze the codebase architecture: 1. Map all internal imports and build dependency graph 2. Identify layer hierarchy (which packages depend on which) 3. Extract key interfaces, types, and abstractions 4. Trace 3-5 critical code paths end-to-end 5. Catalog error handling patterns 6. Detect any circular dependencies (P0 issue!) Tech stack: {TECH} Output: JSON summary + detailed findings Save results to: harness/.analysis/architecture.json """) Agent("harness-state-analysis", prompt=""" Audit existing harness infrastructure: 1. Check AGENTS.md: exists? accurate? right size (80-120 lines)? 2. Check docs/: ARCHITECTURE.md accuracy, design docs coverage 3. Check scripts/lint-*: layer map coverage, error message quality 4. Check harness/: eval tasks, trace format, memory structure 5. Score each dimension (0-10) 6. List gaps with priority (P0/P1/P2/P3) Output: JSON audit report with scores and gaps Save results to: harness/.analysis/audit.json """) Agent("environment-analysis", prompt=""" Detect runtime environment requirements: 1. Scan dependencies for DB drivers (postgres, mysql, sqlite, mongo) 2. Scan for service SDKs (redis, kafka, aws, gcp) 3. Find all environment variable references 4. Check for existing docker-compose.yml or k8s configs 5. Identify required secrets (never expose values!) Output: JSON environment spec Save results to: harness/.analysis/environment.json """) 2.2 Wait for Analysis Completion The agents will notify when done. While waiting, you can: Review any existing documentation Prepare templates for Phase 4 2.3 For Empty Projects Skip Phase 2 analysis agents. Instead: Use templates from references/greenfield-templates.md Base decisions on user's tech stack choice Design a standard 3-layer architecture Phase 3: Delta Synthesis Goal : Merge analysis results and compute exactly what needs to be created/updated. 3.1 Read Analysis Results cat harness/.analysis/architecture.json cat harness/.analysis/audit.json cat harness/.analysis/environment.json 3.2 Compute Delta Create a delta list: ## Delta: What Needs to Be Done ### To Create (doesn't exist) - [ ] AGENTS.md - [ ] docs/ARCHITECTURE.md - [ ] scripts/lint-deps.go - [ ] harness/config/environment.json ### To Update (exists but has gaps) - [ ] docs/DEVELOPMENT.md — missing build commands - [ ] scripts/lint-quality.py — missing 3 packages in layer map ### Already Good (no changes needed) - [x] Makefile — has all required targets - [x] .github/workflows/ci.yml — properly configured 3.3 Confirm with User (if AskUserQuestion available) For significant changes: { "question" : "I've analyzed the codebase. Ready to proceed with these changes?" , "header" : "Confirm" , "multiSelect" : false , "options" : [ { "label" : "Yes, proceed with all" , "description" : "Create/update all identified items" } , { "label" : "Show me the details first" , "description" : "I'll explain what each change involves" } , { "label" : "Only critical items" , "description" : "Just P0/P1 items, skip P2/P3 for now" } ] } Phase 4: Parallel Creation/Update Goal : Create or update all harness files through parallel agents. 4.1 Spawn Creation Agents Based on the delta, spawn appropriate agents in parallel : Agent("create-documentation", prompt=""" Create/update documentation files based on analysis: Architecture data: {from architecture.json} Existing state: {from audit.json} Delta items: {documentation items from delta} Files to create/update: 1. AGENTS.md — 80-120 lines, navigation map with numbered sections 2. docs/ARCHITECTURE.md — Mermaid diagrams from actual imports, layer table 3. docs/DEVELOPMENT.md — Real build/test/lint commands 4. docs/design-docs/*.md — For each key component Requirements: - Every claim must cite file:line from codebase - No placeholders — real, useful content only - Use templates from references/documentation-templates.md Working directory: {cwd} """) Agent("create-linters", prompt=""" Create/update linter scripts based on analysis: Architecture data: {from architecture.json - especially layer hierarchy} Existing linters: {from audit.json} Delta items: {linter items from delta} Files to create/update: 1. scripts/lint-deps.{ext} — Layer map with ALL packages from analysis 2. scripts/lint-quality.{ext} — Code quality rules Requirements: - Layer map must include EVERY package (no blind spots) - Error messages MUST be agent-actionable: WHAT + WHY + HOW - Use templates from references/linter-templates.md Tech stack: {TECH} Working directory: {cwd} """) Agent("create-harness-config", prompt=""" Create/update harness configuration based on analysis: Environment data: {from environment.json} Architecture data: {from architecture.json} Existing state: {from audit.json} Delta items: {config items from delta} Files to create/update: 1. harness/config/environment.json — Runtime ecosystem contract (v2.0 schema) 2. harness/scripts/setup-env.sh — Start dependencies 3. harness/scripts/start-server.sh — Start app 4. harness/scripts/teardown-env.sh — Cleanup 5. Makefile targets — lint-arch, build, test 6. .github/workflows/ci.yml — CI integration IMPORTANT: Do NOT create harness/config/verify.json — verification configuration is dynamically generated by harness-executor at task runtime based on environment.json + task context (which files changed, what the task was). Requirements: - Follow environment collection guide from references/environment-config-guide.md - Use ${VAR_NAME} for all secrets, never hardcode - Scripts must be executable and self-contained - Collect critical info (startup command, required services) via AskUserQuestion if not detectable - Write TODO placeholders for optional missing config Working directory: {cwd} """) 4.2 For Empty Projects: Also Create Business Code Plan For empty projects, add one more agent: Agent("create-exec-plan", prompt=""" Create execution plan for business code (harness-executor will implement this): Tech stack: {TECH} Project type: {from user choice} Architecture: 3-layer (Types → Core → Entry Points) Create: docs/exec-plans/active/bootstrap-code.md Contents: - Full source code for initial project structure - main.go/index.ts/main.py entry point - Basic types and core logic - Test files This is for harness-executor to implement — not harness-creator's responsibility. """) 4.3 Wait for Creation Completion Agents will notify when done. Collect any issues they encountered. Phase 5: Verification + Handoff Goal : Ensure everything works, then hand off or present results. 5.1 Run Verification # 1. Build passes go build ./... || npm run build || python -m compileall . # 2. Linters pass make lint-arch # 3. AGENTS.md size check wc -l AGENTS.md # Should be 80-120 lines # 4. All expected files exist test -f AGENTS.md && echo "✓ AGENTS.md" test -f docs/ARCHITECTURE.md && echo "✓ ARCHITECTURE.md" test -f scripts/lint-deps* && echo "✓ lint-deps" test -d harness/ && echo "✓ harness/" # 5. Design docs exist (not just index) find docs/design-docs -name "*.md" ! -name "index.md" | wc -l 5.2 Present Summary ## Harness Infrastructure Complete **Project** : {project-name} **Tech Stack** : {TECH} **Files Created/Updated** : {count} ### Created Files - AGENTS.md ({N} lines) - docs/ARCHITECTURE.md - docs/DEVELOPMENT.md - docs/design-docs/{component}.md - scripts/lint-deps.{ext} - scripts/lint-quality.{ext} - harness/config/environment.json - Makefile ### Verification Results - Build: ✓ - make lint-arch: ✓ - AGENTS.md size: ✓ ({N} lines) ### Next Steps
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下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |