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

No annotations are provided, so the description must carry the burden of behavioral disclosure. It states the tool retrieves code samples from 'official Microsoft Learn documentation' and emphasizes 'LATEST OFFICIAL' snippets, which adds source context. However, it does not explain the return format, pagination, rate limits, or how to handle cases with no results, leaving some behavioral aspects undisclosed.

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-organized with clear sections for purpose, usage, and pattern. It front-loads the core function and uses bullet points for readability. Minor redundancy like the duplicated language list and the phrase 'empower coding capabilities' add slight fluff, but the overall structure keeps it efficient.

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?

For a simple search tool with only two parameters and no output schema, the description provides sufficient context: what it does, when to use it, and how parameters work. It lacks explicit mention of result format or error behavior, but given the tool's simplicity, the coverage is adequate.

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%, with both query and language parameters fully described. The description's 'Usage Pattern' section adds a note on using descriptive queries or SDK/class/method names, but this largely mirrors the schema. The eligible language values are duplicated from the schema, adding no new semantic information.

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 function: 'Search for code snippets and examples in official Microsoft Learn documentation.' It specifies the resource (Microsoft Learn) and the purpose (retrieving code samples for Microsoft/Azure products), which distinguishes it from sibling tools like microsoft_docs_search that likely search broader documentation.

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 a dedicated 'When to Use This Tool' section with concrete scenarios: 'When you are going to provide sample Microsoft/Azure related code snippets in your answers' and 'When you are generating any Microsoft/Azure related code.' This gives clear usage context, though it does not explicitly mention alternatives or when not to use the tool.

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