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 necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa
Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add davila7/claude-code-templates --skill "agent-tool-builder" -g -a claude-code -yOr manually — copy the SKILL.md below into:
~/.claude/skills/agent-tool-builder-davila7/SKILL.md---
name: agent-tool-builder
description: "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 necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa"
source: vibeship-spawner-skills (Apache 2.0)
---
# 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`
Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses (e.g. hermes-agent@agentmail.to).
AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.
Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).