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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral details: returns up to 10 chunks, each max 500 tokens, sourced from Microsoft Learn and official sources, and includes title, URL, and self-contained excerpt. This goes beyond annotations by specifying output limits and content format, making agent invocation expectations precise.

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 well-structured, leading with the core purpose, then operational details, and ending with a follow-up pattern. It is appropriately sized and front-loaded, though a few phrases like 'high-quality' and 'optimized for fast retrieval' add mild redundancy. Still, every sentence earns its place.

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 has a rich output schema (title, URL, excerpt), and while the description does not repeat the schema, it adds context on result count and token limits. The follow-up pattern with fetch tool makes the overall workflow complete. It lacks mention of edge cases (e.g., empty query) but overall covers the essentials for a search 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?

With 100% schema description coverage, the baseline is 3. The tool description does not add new semantic details about the query parameter; it only repeats the purpose. The parameter is already well-defined in the schema, so the description neither enhances nor obscures meaning.

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 opens with 'Search official Microsoft/Azure documentation to find the most relevant and trustworthy content for a user's query,' which names a specific verb (search) and resource (Microsoft/Azure docs). It clearly distinguishes this tool from its siblings by highlighting the search mechanism and the excerpt-based results, with explicit mention of the complimentary fetch tool in the follow-up pattern.

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 explicit guidance: 'Always use this tool to quickly ground your answers' and directs users to microsoft_docs_fetch for full detail, even calling it a 'required step for comprehensive results.' This gives a clear when-to-use and when-to-use-alternative strategy, which is stronger than simply implied usage.

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