find_tool_mentions

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

No annotations are provided, so the description carries the full burden. It discloses the return fields (tool names, descriptions, GitHub URLs, issue context) and the optional filter. It does not mention sorting or pagination, but for a read-oriented find tool, the description offers adequate behavioral detail.

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?

Two sentences, front-loaded with the main action and scope. No redundant wording or unnecessary details.

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?

The tool is simple with two optional parameters, no output schema, and no annotations. The description covers what it does, what it returns, and how to filter. It is complete enough for an agent to determine if this tool fits the task.

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% for both parameters (limit and query). The description only restates the query's search purpose ('find tools related to a specific technology or capability') without adding new meaning beyond the schema.

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's purpose with a specific verb 'Find' and explicit resources: community tools, GitHub projects, and Microsoft AI products/features mentioned in the Microsoft AI Roundup. This distinguishes it from siblings like get_issue and list_issues, which focus on issues.

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 provides clear context: it searches tool mentions within the Microsoft AI Roundup, with an optional keyword filter. However, it does not explicitly mention when to use an alternative like search_microsoft_ai_roundup, lacking direct exclusionary guidance.

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