Skills › AI & Agent Engineering › RAG & retrieval
search-first
Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.
Tools: textlint-rule-no-dead-link
The full skill
—
name: search-first
description: Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.
origin: ECC
—
# /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
“`
┌─────────────────────────────────────────────┐
│ 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
### 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:
“`
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
")
“`
## 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`/`got` (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
– **Over-customizing**: Wrapping a library so heavily it loses its benefits
– **Dependency bloat**: Installing a massive package for one small feature