search-first
Skill11 starsChanged 4 months agoMITView on GitHub
Use before writing custom code or a research workflow when a maintained library, tool, skill, or proven pattern may already exist. Start with local reuse and targeted evidence; broaden to external research for new dependencies, new mechanisms, or uncertain external facts.
42 other projects use a version of this, 25 of them edited.
Adopted by
Most recently taken up by
- Rojios/everything-claude-codeedited, first seen Nov 8, 2026
- shimo4228/akc-cycletheir own version, first seen Nov 8, 2026
- pankaj-mahaur/Agent-Daemonedited, first seen Nov 6, 2026
- matheus-rib1108/meu-kit-claude-codeedited, first seen Nov 1, 2026
- TsinHzl/claude-code-configtheir own version, first seen Nov 1, 2026
- shimo4228/search-firsttheir own version, first seen Nov 1, 2026
Used with
Projects with it also use continuous-agent-loop, agent-harness-construction and 9 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
junimnjwSkillcontinuous-agent-loop
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
Also in 4 projects that use this
junimnjwSkillagent-harness-construction
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Also in 4 projects that use this
loulanyueSkillsafety-guard
Also in 3 projects that use this
loulanyueSkillrules-distill
Scan skills to extract cross-cutting principles and distill them into rules — append, revise, or create new rule files
Also in 3 projects that use this
dcs-soniSkillcodebase-onboarding
Help developers understand unfamiliar codebases quickly. Use when
Also in 3 projects that use this
MicrosoftSkillerror-handling
统一错误处理系统。在添加 API 端点、修改错误处理、添加前端 API 调用、编写错误相关测试时使用。
Also in 3 projects that use this
- +2 more from junimnjw
Other versions42 projects use a version of this.
Word for word · 0
None found.
Edited · 25
- loulanyue/awesome-claude-notes★ 27264% same
- Fmarzochi/EGC★ 6164% same
- jiten-singh-shahi/salesforce-claude-code★ 1518% same
- frankxai/agentic-creator-os★ 1064% same
- DetectHensenberg/RAG4JZDQ★ 864% same
- gongyijie85/dsh-ecc★ 866% same
- VoVuongThanhDat/agentflow★ 864% same
- chadixearth/graphyloop★ 366% same
- bjornjee/skills★ 238% same
- themusecatcher/ai-coding-kit★ 265% same
15 more not listed
Wrote their own version · 17
- songjiun10-collab/Senior-thinking-skills★ 87same name
- LeeYudok/agents-scaffold★ 38same name
- YehudaFrankel/clankbrain★ 16same name
- arsen-ask-lx/Agent_Quality_Kit★ 4same name
- shimo4228/claude-harness★ 4same name
- shimo4228/search-first★ 4same name
- Yog-Sotho/claude-skills★ 4same name
- Saddss/cursor-skills★ 2same name
- shimo4228/akc-cycle★ 2same name
- TsinHzl/claude-code-config★ 2same name
7 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository17 other files it gives its agents.
- app-bug-forensicsSkill
- app-feature-craftSkill
- app-release-readinessSkill
- codex-session-restoreSkill
- design-taste-frontendSkill
- experiment-plannerSkill
- feishu-paper-readingSkill
- github-project-releaseSkill
- grill-meSkill
- paper-framework-figure-studio-proSkill
- paper-review-panelSkill
- paper-share-htmlSkill
- paper-visual-craftSkill
- paper-writingSkill
- rebuttal-response-skillsSkill
- research-evidenceSkill
- ui-ux-pro-maxSkill
The file
We split this skill into the rules it gives an agent
12 rules. 4 are common, 5 are distinctive, and 3 are very specific to this project.
4
Common
Most of the 36 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 13
Use this skill when:
- Common: line 17
Before creating a new utility, helper, or abstraction
- Distinctive: line 67
Start with the repository and approved local catalog.
- Very specific: line 102
When the task needs research grounding, method positioning, related work, citation support, or top-venue precedent, use $research-evidence …
- Very specific: line 109
Use the evidence result to decide Adopt, Extend, Compose, or Build only when the Research Gate calls for external evidence.
- Distinctive: line 111
Do not claim literature coverage when the research-evidence tool or source channel was unavailable.
- Common: line 116
Before writing a utility or adding functionality, mentally run through:
- Distinctive: line 134
Do not launch the full researcher workflow for routine fixes, result fills, or known local reuse.
- Distinctive: line 149
Use the current agent or subagent tool exposed by the active harness.
- Very specific: line 163
Document processing → unstructured, pdfplumber, mammoth
- Distinctive: line 190
When broader research is warranted, combine for progressive discovery:
- Common: line 230
Ignoring MCP: Not checking if an MCP server already provides the capability
“Common” is measured: kept by at least 6 in 10 of the 36 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
/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. NEED + LOCAL REUSE GATE │
│ Inspect approved local implementations │
│ and results before external searching │
├─────────────────────────────────────────────┤
│ 1. RESEARCH DECISION │
│ Decide whether reuse, targeted lookup, │
│ or broader research is actually needed │
├─────────────────────────────────────────────┤
│ 2. TARGETED SEARCH (only when warranted) │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Registry │ │ Tools / │ │ GitHub / │ │
│ │ / docs │ │ skills │ │ evidence │ │
│ └──────────┘ └──────────┘ └──────────┘ │
├─────────────────────────────────────────────┤
│ 3. EVALUATE │
│ Score candidates (functionality, maint, │
│ community, docs, license, deps) │
├─────────────────────────────────────────────┤
│ 4. DECIDE │
│ ┌─────────┐ ┌──────────┐ ┌─────────┐ │
│ │ Adopt │ │ Extend │ │ Build │ │
│ │ as-is │ │ /Wrap │ │ Custom │ │
│ └─────────┘ └──────────┘ └─────────┘ │
├─────────────────────────────────────────────┤
│ 5. IMPLEMENT │
│ Reuse approved solution or write the │
│ smallest justified custom code │
└─────────────────────────────────────────────┘Decision Matrix
| Signal | Action |
| Approved local implementation or result | Reuse or repair — no broad fresh search required |
| Specific local gap or uncertainty | Targeted lookup — search only for that issue |
| New dependency, new mechanism, or uncertain external fact | Research — compare evidence before deciding |
| Exact match, well-maintained, MIT/Apache | Adopt — use directly when available or within authorized implementation scope |
| Partial match, good foundation | Extend — add a thin wrapper within authorized implementation scope |
| Multiple weak matches | Compose — combine 2-3 small packages |
| Nothing suitable found | Build — write custom, but informed by research |
Research Gate
Start with the repository and approved local catalog. Inspect existing modules, tests, lockfiles, configured tools or skills, prior results, and known patterns before searching externally. If an approved implementation or result already meets the need, reuse it. For a known defect or result gap, repair or fill it and use a targeted lookup only when a specific external fact or compatibility question remains; do not force a broad external search or launch the full researcher workflow for every fix.
Broader research is warranted when selecting a new dependency, introducing a new mechanism or architecture, or relying on external facts that may be uncertain or changed. Delegate only a bounded, independent search that would materially improve the decision. For search-only or advisory work, do not turn a recommendation into an automatic package install, configuration change, publication, message, or other external mutation. For an implementation request, ordinary project-scoped dependency installation and configuration are allowed within the existing task authority and budget; ask before global or system changes, new external effects, or scope or cost expansion.
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 |
| Skill catalog | Inspect the active harness's available skills or configured skill root | Say no local skill catalog was available |
Academic Literature Path
When the task needs research grounding, method positioning, related work,
citation support, or top-venue precedent, use $research-evidence instead of
ad hoc web search. Prefer CVPR, ICCV, ECCV, ICLR, NeurIPS/NIPS, and ICML for
CV/ML work; include CoRL, ICRA, IROS, AAAI, IJCAI, T-ITS, and RA-L only when
the user topic justifies autonomous-driving, robotics, or collaborative
perception coverage.
Use the evidence result to decide Adopt, Extend, Compose, or Build only
when the Research Gate calls for external evidence.
Do not claim literature coverage when the research-evidence tool or source
channel was unavailable.
Quick Mode (inline)
Before writing a utility or adding functionality, mentally run through:
- Is there an approved implementation or result locally? → Inspect relevant modules, tests, configs, and outputs first; reuse or repair it.
- Is there a specific gap or uncertainty? → Run a targeted lookup only if it would change the decision.
- Is a new dependency or mechanism, or an uncertain external fact involved? → Research the relevant registries, docs, or evidence.
- Is there an MCP or connected tool for this? → Inspect the active tool list and relevant configuration when research is warranted.
- Is there a skill for this? → Inspect the active harness's skill catalog.
- Is there a GitHub implementation/template? → Search maintained OSS when the Research Gate calls for it before writing net-new code.
Full Mode (agent)
For non-trivial functionality that passes the Research Gate, launch the researcher agent only when a bounded, independent search would materially help. Do not launch the full researcher workflow for routine fixes, result fills, or known local reuse.
Agent(subagent_type="general-purpose", prompt="
Research existing tools for: [DESCRIPTION]
Language/framework: [LANG]
Constraints: [ANY]
Search: relevant package registries, connected tools, agent skills/catalog,
GitHub, official docs, or academic evidence
Return: A bounded comparison with recommendation and evidence gaps
")Use the current agent or subagent tool exposed by the active harness. If no delegation tool is available, run the same bounded search channels directly.
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
- Provider SDKs → official documentation or the configured documentation tool
- 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) when the Research Gate calls for external research:
- 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, when warranted, for:
- Technology stack decisions
- Integration pattern discovery
- Existing reference architectures
With iterative-retrieval skill
When broader research is warranted, 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 — recommend textlint-rule-no-dead-link; install it within an
authorized project implementation
Result: Zero custom code, battle-tested solutionExample 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 — recommend got/httpx directly with retry config; apply it within
an authorized project implementation
Result: Zero custom code, production-proven librariesExample 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 — recommend ajv-cli; use it within an authorized project
implementation, then write a project-specific schema
Result: 1 package + 1 schema file, no custom validation logicAnti-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
- Forced discovery: Running broad external search or the full researcher for a routine local fix or result fill
- Unbounded delegation: Sending vague research tasks without an independent, decision-relevant deliverable
- Unauthorized mutation: Installing, configuring, publishing, or sending anything merely because a recommendation was made
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

