agentminds_agent_detail

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the type of data returned (metrics, warnings, patterns, recommendations), which is helpful. However, it does not explicitly state that the tool is read-only or describe any potential side effects, performance considerations, or error conditions. For a get operation, the transparency is adequate but not exceptional.

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 very concise: two sentences with no filler. The first sentence states the core purpose, and the second provides usage context with examples. Every word serves a purpose, achieving high efficiency.

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 that there is no output schema, the description compensates by listing the categories of information returned (metrics, warnings, patterns, recommendations). This gives the agent a clear expectation of the output. However, it does not mention any pagination, error handling, or field-level details, which would be needed for a perfect score. Still, it is adequate for a detail-fetching 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?

The input schema has 100% description coverage, so the baseline is 3. The description adds context by listing example agent names (health, security, etc.) and implying the need for a specific query. However, it does not provide additional meaning beyond what the schema already offers (e.g., site_id is a string, agent_name has a definitive list). The value-add is marginal.

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: 'Get detailed info about a specific agent — metrics, warnings, patterns, recommendations.' It uses a specific verb 'get' and a clear resource 'detailed info about a specific agent,' which distinguishes it from sibling tools like agentminds_site_overview (site-level overview) and agentminds_status (general status). The addition of Turkish example queries further clarifies the intended use.

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 states when to use the tool: 'Use when user asks about a specific agent...' and provides concrete example queries. However, it does not explicitly mention when not to use it or list alternatives among the sibling tools, which would have elevated the score to 5.

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