Find Real-World Code Examples

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the tool as read-only, non-destructive, idempotent, and open-world. The description adds behavioral context beyond annotations: it searches GitHub, requires authentication for higher limits, returns code snippets with attribution, and clarifies the source (open-source repos, not library docs). A minor gap is not mentioning error handling or pagination, but this is sufficient for transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only 4 sentences, each serving a distinct purpose: purpose, output, prerequisites, and usage differentiation. No redundant or vague phrasing. Every sentence adds value, and the structure is front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters (100% schema coverage), no output schema, and annotations covering safety, the description provides sufficient context: source of examples, environment variable requirement, and differentiation from a sibling. It is complete enough for an agent to decide when and how to invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (all 4 parameters have descriptions). The description adds minimal extra meaning beyond the schema: it rephrases 'library' and 'pattern' but does not provide additional semantic context (e.g., example values or constraints). Baseline 3 is appropriate since schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches GitHub for real-world usage examples of libraries or patterns, and distinguishes itself from gt_snippets by specifying the source (open-source repos vs library docs). This provides a specific verb-resource pair and sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use ('when you want to see how real projects use a library') and when not to (directing to gt_snippets for library-doc examples). It also mentions the required GT_GITHUB_TOKEN environment variable for higher rate limits, providing clear guidance on prerequisites and alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.