Agent skill · software engineering · aiskillstore
building-agent-tools
Guide for creating effective tools for AI agents. Use when building MCP tools, agent APIs, or any tool interface that agents will consume. Focuses on token efficiency, meaningful context, and proper namespacing.
Why this skill is useful
Provides specific design principles and patterns for creating efficient tools that enhance agent capabilities, which the AI wouldn't reliably generate on its own.
What it needs
About 2k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Building Tools for AI Agents Workflow 1. Define Purpose Identify what agents need to accomplish with this tool Determine if existing tools can be consolidated Plan the tool's interface for agent consumption 2. Design Interface Choose descriptive, namespaced tool names Define parameters with clear types and descriptions Design output format for maximum signal, minimum tokens 3. Implement Build with token efficiency in mind Add pagination, filtering, sensible defaults Return semantic identifiers, not raw IDs 4. Validate Test with real agent workflows Check token consumption patterns Verify error messages guide agents toward solutions Design Principles Tool Consolidation More tools don't lead to better outcomes Combine related operations into single tools Example: scheduleevent that checks availability AND creates event Avoid simple CRUD-style tools that require multiple calls Namespacing Prefix related tools with service name: asanaprojectssearch, asanauserssearch Group by domain to help agents distinguish functionality Use consistent naming patterns across tool families Meaningful Context Return high-signal information, not raw data dumps Resolve cryptic UUIDs to human-readable identifiers Include responseformat parameter (concise/detailed) for flexibility Surface relevant metadata agents need for next steps Token Efficiency Implement pagination with sensible defaults Add filtering parameters to reduce unnecessary data Truncate large responses intelligently Prefer structured output over verbose prose Tool Descriptions Invest heavily in clear, explicit descriptions Describe what the tool does, when to use it, and what it returns Include parameter constraints and valid values Small description improvements yield large performance gains Anti-Patterns Creating many granular tools instead of consolidated operations Returning raw IDs that agents can't interpret Omitting pagination on potentially large result sets Vague tool descriptions that leave agents guessing Error mes …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/building-agent-tools