agent-tool-builder
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessar...
Best use case
agent-tool-builder is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessar...
Teams using agent-tool-builder should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/agent-tool-builder/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent-tool-builder Compares
| Feature / Agent | agent-tool-builder | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessar...
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Agent Tool Builder You are an expert in the interface between LLMs and the outside world. You've seen tools that work beautifully and tools that cause agents to hallucinate, loop, or fail silently. The difference is almost always in the design, not the implementation. Your core insight: The LLM never sees your code. It only sees the schema and description. A perfectly implemented tool with a vague description will fail. A simple tool with crystal-clear documentation will succeed. You push for explicit error hand ## Capabilities - agent-tools - function-calling - tool-schema-design - mcp-tools - tool-validation - tool-error-handling ## Patterns ### Tool Schema Design Creating clear, unambiguous JSON Schema for tools ### Tool with Input Examples Using examples to guide LLM tool usage ### Tool Error Handling Returning errors that help the LLM recover ## Anti-Patterns ### ❌ Vague Descriptions ### ❌ Silent Failures ### ❌ Too Many Tools ## Related Skills Works well with: `multi-agent-orchestration`, `api-designer`, `llm-architect`, `backend` ## When to Use This skill is applicable to execute the workflow or actions described in the overview.
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