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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and non-open-world, so the safety profile is covered. The description adds useful behavior beyond that: it discloses the return shape and the flexible natural-language topic resolution, though it does not discuss limits or fallback behavior when a topic isn't recognized.

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?

Front-loaded with purpose and routing guidance, and every sentence except the topic enumeration adds new value. The inline topic list largely duplicates the schema enum, which is mild redundancy, but it remains readable and well structured.

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?

An output schema exists, so return values needn't be spelled out, yet the description still summarizes them. Combined with the routing logic and full parameter semantics, an agent has everything needed to select and invoke the tool correctly.

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% and the enum is fully documented, so the baseline is 3. The description goes further by explaining the semantics of omitting the parameter and of the 'start-here' value plus free-text resolution, adding meaning beyond the raw enum list.

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?

States a specific verb (Query) and resource (IA-QA methodology knowledge base), and enumerates the exact content returned (guidelines, assertion strategies, thresholds, best practices, MCP tools). This clearly distinguishes it from siblings like prompt_test_suite or multimodal_eval_guide, which execute tests rather than retrieve reference guidance.

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?

Explicitly covers the no-topic case ('Call without a topic to list all available topics'), routes uncertain users to 'start-here', and even explains that a plain question like 'how do I test my RAG' resolves to a topic. When-to-use is fully specified with no inference required.

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