Design LLM-facing tool schemas that prevent hallucination, silent failures, and token waste.
Works with
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
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
Creating clear, unambiguous JSON Schema for tools
Using examples to guide LLM tool usage
Returning errors that help the LLM recover
Works well with: multi-agent-orchestration, api-designer, llm-architect, backend
This skill is applicable to execute the workflow or actions described in the overview.
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionagent-tool-builderExecute 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.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
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.
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.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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agent-tool-builder is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added agent-tool-builder from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
agent-tool-builder reduced setup friction for our internal harness; good balance of opinion and flexibility.
agent-tool-builder fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend agent-tool-builder for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
agent-tool-builder fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: agent-tool-builder is focused, and the summary matches what you get after install.
Useful defaults in agent-tool-builder — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added agent-tool-builder from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
agent-tool-builder has been reliable in day-to-day use. Documentation quality is above average for community skills.
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