Find curated Microsoft Learn documentation for Azure topics and best-practice questions, providing trusted references to resolve governance, RBAC, and Entra ID issues.
Return curated official Microsoft Learn references relevant to an Azure topic or best-practice question.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| topic | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations (readOnlyHint, openWorldHint, idempotentHint) already cover that the tool is read-only and side-effect free. The description adds no further behavioral details beyond the word 'curated', which implies filtering but not its mechanism. No contradictions exist between the description and annotations.
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 a single, concise sentence that directly states the tool's function and input scope. It avoids unnecessary jargon or extraneous details, making it easy to read and understand quickly.
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 description conveys the general purpose but lacks details about the returned data structure, such as whether references are URLs, titles, or snippets, and how they are ordered. Given the absence of an output schema, this omission leaves some ambiguity about the exact format of the response.
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 schema defines 'topic' as a required string and 'limit' as an optional integer with default 4. The description explains that the topic is an Azure topic or best-practice question, giving context to the 'topic' parameter. However, 'limit' is not described at all, leaving its purpose ambiguous despite being a common parameter name.
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 returns curated official Microsoft Learn references for an Azure topic or best-practice question. It specifies the exact resource (Microsoft Learn references) and the subject area (Azure), distinguishing it from sibling tools that focus on identity, roles, or resource inventory.
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 does not provide explicit guidance on when to use this tool versus alternatives. While the sibling list contains many tools, none directly compete as a documentation search tool, so the intended usage is implied but not stated. No mention of prerequisites, typical scenarios, or when to avoid using it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.