mturac /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
┌─────────────────────────────────────────────┐
│ 0. TOOL AVAILABILITY PREFLIGHT │
│ Check search channels before relying on │
│ them; report skipped channels honestly │
├─────────────────────────────────────────────┤
│ 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 │
└─────────────────────────────────────────────┘
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 ~/.codex/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:
- Does this already exist in the repo? →
rgthrough relevant modules/tests first - Is this a common problem? → Search npm/PyPI
- Is there an MCP for this? → Check
~/.codex/settings.jsonand search - Is there a skill for this? → Check
~/.codex/skills/ - 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:
Agent(subagent_type="general-purpose", prompt="
Research existing tools for: [DESCRIPTION]
Language/framework: [LANG]
Constraints: [ANY]
Search: npm/PyPI, MCP servers, OpenAI Codex skills, GitHub
Return: Structured comparison with recommendation
")
Older OpenAI Codex 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
- Codex 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"
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
Example 2: "Add HTTP client wrapper"
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
Example 3: "Add config file linter"
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
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