agent-tool-builder
Design LLM-facing tool schemas that prevent hallucination, silent failures, and token waste.
Works with
What it does
Focuses on JSON Schema design, input examples, and error handling patterns that help LLMs use tools correctly
Emphasizes explicit documentation and clear descriptions over implementation details, since LLMs only see the schema
Identifies anti-patterns like vague descriptions, silent failures, and tool overload that cause agent failures
Covers function-calling, MCP tools, and tool validatio
Installation Guide
How to use agent-tool-builder on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
agent-tool-builder
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches agent-tool-builder from sickn33/antigravity-awesome-skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate agent-tool-builder. Access via /agent-tool-builder in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
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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Use Cases
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort