Tool Scout — find the right tools for your tasks
SkillSearchSearch for tools (services, MCP servers, AI models, no-code platforms, libraries, APIs, GitHub repos, awesome-lists) to solve project tasks. Searches 5 sources: web, GitHub, MCP catalogs, awesome-lists, package registries. Freshness is critical — finds current tools. Triggers: "find tools for...", "what tools can solve...", "tool scout", "best way to do...", "search for services...", "how to build...", "is there a skill for...", "is there an MCP server for...", "find a library for...".
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Tool Scout — find the right tools for your tasks skill
What this skill tells your AI
The instructions your AI receives, as published by alenazaharovaux/share in skills/tool-scout/SKILL.md and read by ahel’s review.
This skill helps discover tools for project tasks. Not everything needs to be built from scratch — a service, MCP server, AI model, library, or no-code platform might already solve your problem.
Searches 5 sources: web search, GitHub, MCP server catalogs, awesome-lists, and package registries. Sources are selected adaptively based on the task type.
Step 0. Configuration (First Run)
Read the config file at ~/.claude/skills/tool-scout/config.md.
If the config file does not exist, run the setup:
Question 1 — Search engine:
Ask the user: "Which web search tool do you have available in Claude Code?"
Options:
- Exa MCP (recommended) — best results, supports both web search and code context search
- WebSearch — built-in Claude Code web search (no setup needed, but less precise)
- Other MCP search — if you have a different search MCP server, specify its tool name
Question 2 — GitHub CLI:
Check automatically: gh --version
- If available →
github_cli: true - If not →
github_cli: false(GitHub search falls back to web queries withsite:github.com)
Question 3 — Language:
Ask the user: "What language should I use for results and communication?" Default: English.
Write answers to ~/.claude/skills/tool-scout/config.md:
search_engine: exa | websearch | other
search_tool_name: mcp__exa__web_search_exa
code_search_tool_name: mcp__exa__get_code_context_exa
github_cli: true | false
language: english
Input
A task or list of subtasks from the user's prompt:
- Free text: "need to build a UI for a dashboard"
- Plan reference: "find tools for tasks 3-5 from the plan"
- Specific subtask: "best way to generate PDF reports"
If a plan file is referenced — read it and extract tasks.
Process
Step 1. Parse input
Identify specific tasks/subtasks from the prompt. If input is a plan file, read it. Formulate each task as a short search phrase.
Step 2. Classify by domain
Group tasks by domain:
- UI/design
- Backend/API
- Data/analytics
- Automation/integration
- Content/text
- Infrastructure/deployment
- Other
Step 3. Search (adaptive source selection)
Determine task type and select sources:
| Task type | Web | GitHub | MCP catalogs | Awesome |
|---|---|---|---|---|
| SaaS/service | + | |||
| Library/package | + | + | + | |
| MCP server | + | + | + | |
| AI tool | + | + | + | |
| Skill/plugin | + | + | + | |
| Unclear | + | + | + | + |
Rule: web + GitHub = always. MCP catalogs and awesome = when relevant. If unsure — include all.
Source 1: Web search (always)
Established tools query:
"best tools for [task] [current year]"
New tools query:
"new AI tool [task] launch [current and previous year]"
Library query (when task needs code):
"best [language] library for [task] [current year]"
This is more effective than site:npmjs.com — comparison articles provide more context than registry pages.
Always use the current year. Never hardcode a specific year.
Source 2: GitHub (always)
If github_cli: true:
gh search repos "[task]" --sort=stars --limit=5gh search repos "[task] tool" --sort=stars --limit=5
If github_cli: false (fallback):
- Web search
site:github.com [task] tool
Source 3: MCP catalogs (when task involves integration, automation, Claude Code)
If github_cli: true:
gh search repos "mcp server [task]" --sort=starsgh search code "[task]" --repo=modelcontextprotocol/servers --filename=README.md
If github_cli: false:
- Web search
"mcp server [task]" site:github.com
Additionally (always):
- Web search
site:smithery.ai [task]
Source 4: Awesome-lists (when looking for curated tool lists)
If github_cli: true:
gh search repos "awesome-[topic]" --sort=stars --limit=3
If github_cli: false:
- Web search
awesome [topic] github
If a relevant awesome-list is found — read the README (first 200 lines) and extract relevant tools.
Parallelism
If there are multiple tasks or domains — run queries across different sources in parallel.
Step 4. Deduplication and table
Compile a single table from results across all sources.
Deduplication: if a tool is found in multiple sources — one row, signals aggregated. Found in multiple places = higher confidence (mention in "Why it fits").
| Task | Tool | Type | Maturity | Signals | Why it fits | Link |
|---|
Tool types:
- MCP server — can be connected to Claude Code
- SaaS/service — external web service
- AI model — specialized neural network
- Library — npm/pip package
- API — external API for integration
- No-code — visual builder
Maturity:
- Established — 1+ year, has community
- New — recently launched, promising
- Archived — repo archived, no longer maintained (red flag)
Signals column:
- ★ GitHub stars (visible in
gh searchresults, no extra API calls) - 🔴 Archived — if repo is archived
Last commit date is NOT a signal of abandonment — small tools and skills are often stable and don't need updates.
npm/PyPI download counts — only in Deep Dive (requires extra API calls).
Step 5. Output and offer deep dive
Display the table in chat. After the table, ask:
Want to dig deeper? Say "dig into [name]". Or ask about a specific source: "any MCP servers for this?", "what about skills?", "any awesome-lists?"
Deep Dive (Level 2)
If the user asks to dig deeper into a specific tool, domain, or source:
-
Launch an Agent tool (subagent) with a detailed prompt:
- Make 5-8 search queries about the tool
- Find: detailed description, usage examples, pricing, limitations, alternatives
- If request targets a specific source ("any skills?") — targeted search via GitHub + awesome
- Get npm/PyPI download counts (if applicable)
- Return a structured report
-
Show result in chat:
[Tool name]
What it is: brief description Price: free / freemium / paid (how much) Maturity: when launched, how many users Signals: ★ stars, downloads, found in [sources] Pros: list Cons/limitations: list Alternatives: list How to integrate: MCP / API / web interface Link: URL
Important
- Communicate in the language specified in config (default: English)
- Freshness is critical — always search for tools from the current and previous year
- Do not recommend dead or abandoned tools (archived, no activity for years)
- If a tool is an MCP server, say so explicitly (can be connected to Claude Code)
- If the task is trivial and better solved with code — say so directly
- Search engine and GitHub CLI are abstracted — check config.md
Signals
- GitHub stars
- 49
- Forks
- 7
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
tool-scout- Source
- github.com/alenazaharovaux/share