Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.

/search first — Research Before You Code Systematizes the "search for existing solutions before implementing" workflow. Trigger Use this skill when: Starting a new feature that likely has existing solutions Adding a dependency or integration The user asks "add X functionality" and you're about to write code Before creating a new utility, helper, or abstraction Workflow Decision Matrix 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 How to Use Step 0: Tool Availability Preflight This is agent guidance, not an executable setup script. Check only the channels that are relevant to the task and project in front of you. Channel Check If missing Repository search rg files and targeted rg queries State that only visible files were inspected Package registry npm version , python m pip version , or project package manager Use web/docs search and avoid claiming registry coverage GitHub CLI gh auth status Use public web or local git history only MCP/docs tools Available tool list or local MCP config Fall back to official docs/web search Skills directory ls ~/.claude/skills ~/.codex/skills where applicable Say no local skill catalog was available Quick Mode (inline) Before writing a utility or adding functionality, mentally run through: 0. Does this already exist in the repo? → rg through relevant modules/tests first 1. Is this a common problem? → Search npm/PyPI 2. Is there an MCP for this? → Check ~/.claude/settings.json and search 3. Is there a skill for this? → Check ~/.claude/skills/ 4. Is there a GitHub implementation/template? → Run GitHub code search for maintained OSS before writing net new code Full Mode (agent) For non trivial functionality, launch the researcher agent: Older Claude Code docs may call this Task(...) ; use the current agent/subagent tool name exposed by the active harness. Search Shortcuts by Category Development Tooling Linting → eslint , ruff , textlint , markdownlint Formatting → prettier , black , gofmt Testing → jest , pytest , go test Pre commit → husky , lint staged , pre commit AI/LLM Integration Claude SDK → Context7 for latest docs Prompt management → Check MCP servers Document processing → unstructured , pdfplumber , mammoth Data & APIs HTTP clients → httpx (Python), ky / undici (Node) Validation → zod (TS), pydantic (Python) Database → Check for MCP servers first Content & Publishing Markdown processing → remark , unified , markdown it Image optimization → sharp , imagemin Integration Points With planner agent The planner should invoke researcher before Phase 1 (Architecture Review): Researcher identifies available tools Planner incorporates them into the implementation plan Avoids "reinventing the wheel" in the plan With architect agent The architect should consult researcher for: Technology stack decisions Integration pattern discovery Existing reference architectures With iterative retrieval skill Combine for progressive discovery: Cycle 1: Broad search (npm, PyPI, MCP) Cycle 2: Evaluate top candidates in detail Cycle 3: Test compatibility with project constraints Examples Example 1: "Add dead link checking" Example 2: "Add HTTP client wrapper" Example 3: "Add config file linter" Anti Patterns Jumping to code : Writing a utility without checking if one exists Ignoring MCP : Not checking if an MCP server already provides the capability Silent skipping : Reporting "nothing found" when a search channel was unavailable Over customizing : Wrapping a library so heavily it loses its benefits Dependency bloat : Installing a massive package for one small feature

search-first