Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Systematizes the "search for existing solutions before implementing" workflow.
Use this skill when:
┌─────────────────────────────────────────────┐
│ 1. NEED ANALYSIS │
│ Define what functionality is needed │
│ Identify language/framework constraints │
├─────────────────────────────────────────────┤
│ 2. PARALLEL SEARCH (researcher agent) │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ npm / │ │ MCP / │ │ GitHub / │ │
│ │ PyPI │ │ Skills │ │ Web │ │
│ └──────────┘ └──────────┘ └──────────┘ │
├─────────────────────────────────────────────┤
│ 3. EVALUATE │
│ Score candidates (functionality, maint, │
│ community, docs, license, deps) │
├─────────────────────────────────────────────┤
│ 4. DECIDE │
│ ┌─────────┐ ┌──────────┐ ┌─────────┐ │
│ │ Adopt │ │ Extend │ │ Build │ │
│ │ as-is │ │ /Wrap │ │ Custom │ │
│ └─────────┘ └──────────┘ └─────────┘ │
├─────────────────────────────────────────────┤
│ 5. IMPLEMENT │
│ Install package / Configure MCP / │
│ Write minimal custom code │
└─────────────────────────────────────────────┘
| Signal | Action |
|---|---|
| Exact match, well-maintained, MIT/Apache | Adopt — install and use directly |
| Partial match, good foundation | Extend — install + write thin wrapper |
| Multiple weak matches | Compose — combine 2-3 small packages |
| Nothing suitable found | Build — write custom, but informed by research |
Before writing a utility or adding functionality, mentally run through:
rg through relevant modules/tests first~/.claude/settings.json and search~/.claude/skills/For non-trivial functionality, launch the researcher agent:
Task(subagent_type="general-purpose", prompt="
Research existing tools for: [DESCRIPTION]
Language/framework: [LANG]
Constraints: [ANY]
Search: npm/PyPI, MCP servers, Claude Code skills, GitHub
Return: Structured comparison with recommendation
")
eslint, ruff, textlint, markdownlintprettier, black, gofmtjest, pytest, go testhusky, lint-staged, pre-commitunstructured, pdfplumber, mammothhttpx (Python), ky/got (Node)zod (TS), pydantic (Python)remark, unified, markdown-itsharp, imageminThe planner should invoke researcher before Phase 1 (Architecture Review):
The architect should consult researcher for:
Combine for progressive discovery:
Need: Check markdown files for broken links
Search: npm "markdown dead link checker"
Found: textlint-rule-no-dead-link (score: 9/10)
Action: ADOPT — npm install textlint-rule-no-dead-link
Result: Zero custom code, battle-tested solution
Need: Resilient HTTP client with retries and timeout handling
Search: npm "http client retry", PyPI "httpx retry"
Found: got (Node) with retry plugin, httpx (Python) with built-in retry
Action: ADOPT — use got/httpx directly with retry config
Result: Zero custom code, production-proven libraries
Need: Validate project config files against a schema
Search: npm "config linter schema", "json schema validator cli"
Found: ajv-cli (score: 8/10)
Action: ADOPT + EXTEND — install ajv-cli, write project-specific schema
Result: 1 package + 1 schema file, no custom validation logic
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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
中文简介正在准备中。当前显示原文说明。
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
中文简介正在准备中。当前显示原文说明。
Engineering operating model for teams where AI agents generate a large share of implementation output.
中文简介正在准备中。当前显示原文说明。
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
中文简介正在准备中。当前显示原文说明。
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.
中文简介正在准备中。当前显示原文说明。
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
中文简介正在准备中。当前显示原文说明。