search_issues

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

With no annotations, the description takes on the transparency burden. It discloses that the tool searches across all repositories the token can see, which is a key behavioral trait. However, it does not mention pagination behavior or result ordering, though the schema covers page and limit.

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 three sentences long, each with a distinct purpose: stating the action, providing use cases, and contrasting with a sibling. No extraneous information.

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's complexity (6 parameters, no output schema), the description effectively covers the cross-repo search nature, use cases, and sibling differentiation. It does not mention return format or ordering, but the schema handles pagination.

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?

The input schema has 100% description coverage, so baseline is 3. The description adds value beyond the schema by explaining how to use the 'type' parameter to exclude pull requests, which is not in the schema description.

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 issues and pull requests across all repositories using keyword, type, state, and labels. It distinguishes from the sibling tool list_issues by advising to use that for single-repo listing.

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 'Use for 'find issues about X' or duplicate detection across repos' and provides the tip to set type='issues' to exclude pull requests. It also tells when not to use it: for listing one repo's issues use list_issues instead.

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