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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/signalo-rust-search-first-4564ce
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing, research, productivity, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/search-first
What's inside
- Skill name
search-first- Description
- Research-before-coding workflow. Search for existing tools / libraries / patterns BEFORE writing custom code. 4 channels: repo search + npm/PyPI + MCP + GitHub.
- License
- MIT
- Instructions
- 172 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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 ~/.claude/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 local MCP config and search 3. Is there a skill for this? → Check the local skills directory 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 a researcher agent: ``` Research existing tools for: [DESCRIPTION] Language/framework: [LANG] Constraints: [ANY] Search: npm/PyPI, MCP servers, agent 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 - SDK docs → a docs MCP 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 a planner agent The planner should invoke a researcher before the Architecture Review phase: - Researcher identifies available tools
From signalo-rust/agent-guardrails, MIT.
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Before committing changes that touch workspace deps, DB schema, or >500 LOC — verify a real clean build.
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Lint checklist for money fields in a billing subsystem.
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Run a practical quality gate before closing work — typecheck, sync/consistency check, and task-specific validation.
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regex-vs-llm-structured-text
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Decision framework for parsing structured text — regex covers 95-98% cheaply and deterministically, and an LLM handles only the low-confidence edge cases.
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jul 11, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/signalo-rust/agent-guardrails
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
More from signalo-rust
- 0.497score
anti-bug-prevention
signalo-rust
Production deploy safety pipeline.
SkillCFreshness: C★ 1Claude Code +9 - 0.497score
api-contract-audit
signalo-rust
Inventory every API endpoint that surfaces a field to clients BEFORE dropping, renaming, or semantically changing it.
SkillCFreshness: C★ 1Claude Code +9 - 0.497score
brainstorm-first
signalo-rust
Before starting any non-trivial task (>0.5 day, new feature, new UI page, new integration, refactor spanning >5 files), it is mandatory to ask the requester…
SkillCFreshness: C★ 1Claude Code +9 - 0.497score
content-hash-cache-pattern
signalo-rust
Cache expensive file processing results via SHA-256 content hashes — path-independent, auto-invalidating, service layer separation.
SkillCFreshness: C★ 1Claude Code +9 - 0.497score
docker-push-verify
signalo-rust
After `docker buildx build --push`, always verify the image actually landed on the upstream registry.
SkillCFreshness: C★ 1Claude Code +9 - 0.497score
eval-harness
signalo-rust
Formal eval-driven development (EDD) framework.
SkillCFreshness: C★ 1Claude Code +9
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
search-first skill. Agent Mart. https://agentmart.dev/skills/signalo-rust-search-first-4564ce (last updated 2026-10-24)