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

The description goes well beyond the annotations. It explains the activation mechanism (notifications/tools/list_changed), the in-memory matching behavior, the cost (no API call, ~3ms), and the idempotent nature (free to call as often as needed). It also warns about a potential failure mode (client not acting on the notification) and how to handle it. This is rich behavioral context that annotations alone don't provide.

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 dense but well-organized, front-loading the core purpose and then providing usage details. It's longer than ideal, but every sentence earns its place: the search strategy, activation mechanism, fallback to qase_api, and cost note are all actionable. The only minor issue is that the cost and 'free to call' details could be seen as slightly redundant with the idempotentHint annotation, but they add practical context.

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 discovery tool with an output schema and rich annotations, the description is complete. It covers what the tool does, how to use it effectively, what to expect after activation, and how to handle edge cases. The output schema presumably describes the list of activated tools, so the description doesn't need to explain return values. Nothing an agent needs to call this correctly is missing.

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 coverage is 100%, so the schema already documents all three parameters. The description adds value by explaining the query matching semantics (every word must appear in a tool's name or description) and the activation default behavior. It doesn't add much about the category parameter, but the schema's enum and description cover that adequately. The description's query guidance is genuinely useful 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: find and activate hidden tools. It uses a specific verb ('find and switch on') and resource ('tools that are hidden by default'), and distinguishes itself from siblings by explaining that only core tools appear in the list and this tool discovers the rest. It also names the sibling qase_api as an alternative for a specific scenario, which helps an agent differentiate.

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 on when to use this tool: whenever a capability seems missing, search here first before concluding it's absent. It also gives concrete search strategies (use two or three words, every word must match) and explains when to use qase_api instead (if activation notification wasn't acted on). This is exemplary usage guidance.

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