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By dragon1086
Automatically scan Claude Code environments to discover native tools and MCP servers, amplify prompts with detected capabilities, and get tailored, non-binding suggestions for optimal tool combinations when asking 'what tools to use' or 'best approach'.
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Discover your tool environment. Amplify your capabilities. (Claude Code + Codex)
Tool Advisor scans your runtime environment — MCP servers, skills, plugins, CLI tools — and suggests optimal tool compositions as non-binding options with copy-paste commands. It arms the model with knowledge it wouldn't otherwise have.

Option 1: One-line install (default: Claude Code + Codex)
curl -fsSL https://raw.githubusercontent.com/dragon1086/claude-skills/main/install.sh | bash
Install for a single agent:
# Codex only
curl -fsSL https://raw.githubusercontent.com/dragon1086/claude-skills/main/install.sh | bash -s -- --agent codex
# Claude Code only
curl -fsSL https://raw.githubusercontent.com/dragon1086/claude-skills/main/install.sh | bash -s -- --agent claude-code
Option 2: Via skills.sh
npx skills add dragon1086/claude-skills -y --agent claude-code
npx skills add dragon1086/claude-skills -y --agent codex
To update, run the same command again.
Just ask naturally:
"Analyze with tool-advisor: refactor the auth module"
"tool-advisor, how should I tackle this database migration?"
"What's the best approach for implementing user authentication?"
"Use $tool-advisor to analyze this task: ship v2 API migration"
The skill activates when you mention tool-advisor or ask for tool recommendations.
Your Prompt
↓
┌──────────────────────────────────┐
│ Tool Advisor v3.4 │
│ "Amplifier, not Commander" │
├──────────────────────────────────┤
│ 1. Discover Environment │
│ MCP / Skills / Plugins / CLI │
│ 2. Analyze Task + Done When │
│ 3. Match Capabilities │
│ 4. Suggest Options (up to 3) │
│ 5. Identify Gaps │
│ 6. Performance Tips │
└──────────────────────────────────┘
↓
Options + Quick Action table
| Feature | Description |
|---|---|
| 4-Layer Environment Scan | Discovers MCP servers, skills, plugins, and CLI tools at runtime |
| Completion Criteria | Extracts "Done when" from prompts so the model knows the finish line |
| Scale-Adaptive Output | Small tasks get <10 lines; large tasks get full analysis |
| Multi-Option Suggestions | Up to 3 approaches (Methodical / Fast / Deep) — never mandates |
| Capability Gap Analysis | Suggests missing tools with "doable without these" disclaimer |
| Iron Rules & Anti-Patterns | 9 hard boundaries prevent advisor-to-executor drift; 3 concise anti-patterns |
| Phase Enforcement | Every phase MUST produce output or explicit "N/A" — no skipping allowed |
| Human-in-the-loop | Never installs without your approval |
Input:
Analyze with tool-advisor: Refactor auth module to use JWT tokens
Output:
## Tool Advisor v3.4 — Environment & Composition Analysis
Prompt: `Refactor auth module to use JWT tokens`
### Your Environment
| Layer | Available |
|-------|-----------|
| MCP Servers | lsp, context7 |
| Skills | /feature-dev, /code-review, /tdd |
| Plugins | oh-my-claudecode (33 agents) |
| CLI | git, node, pytest, docker |
### Task Profile
- **Type**: Modification / **Scale**: Large / **Traits**: Needs planning, has tests
- **Done when**: all session-based auth replaced with JWT, tests pass, no session imports remain
### Relevant Capabilities
- `lsp_diagnostics` — Type-check after changes
- `ast_grep_search` — Find all session usage patterns
- `/feature-dev` — Guided development workflow
### Suggested Approaches
**A — Methodical** (Recommended)
Task(Explore) -> EnterPlanMode -> Edit in stages -> Bash(pytest)
**B — Skill-guided**
/feature-dev (handles the full flow)
**C — Agent-parallel**
[Task(Explore, bg), WebSearch("JWT best practices")] -> plan -> implement
---
## Quick Action
| Approach | Copy & Paste |
|----------|--------------|
| Methodical | Start with `Task(Explore)` to scout the codebase |
| Skill-guided | `/feature-dev` then describe the refactoring |
| Fast | `Glob("**/auth/**") + Grep("session")` parallel |
-> Recommended: "Methodical" (large refactoring benefits from planning first)
MIT © 2026 dragon1086
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