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

Beyond the annotations (read-only, idempotent), the description adds concrete behavioral details: it 'Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples)' and notes that results are 'ready to call directly, no second schema lookup needed.' This gives agents a clear expectation of the tool's output and immediate usability. It does not mention rate limits or ranking logic, but annotations cover the safety profile.

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 front-loaded with 'Find tools by describing the data or task' and then provides a useful domain list and return-format details. While the domain list is somewhat long, it is purposeful in helping agents recognize applicable topics. Every sentence adds value; no fluff.

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 six parameters (mostly aliases) and no output schema, the description sufficiently covers what is returned (top-N tools with full schemas) and when to use it. The input schema already provides examples and alias handling. It could have specified default/max limit textually, but that is in the schema. Overall, the description provides enough context for correct invocation.

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% and already documents all parameters, including aliases for 'query' (q, task, search, description) and the 'limit' range. The description adds only a high-level statement that the tool takes a 'description of what you want to do,' which aligns with the schema but does not add new semantics beyond it. The schema carries the full weight, so the baseline of 3 is appropriate.

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 with a specific verb and resource: 'Find tools by describing the data or task.' It distinguishes itself from sibling tools by explicitly positioning itself as a discovery layer (e.g., 'Call this FIRST when you have many tools available'), which is unique among the listed siblings that are direct data tools.

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?

Provides explicit guidance on when to use: 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This clearly frames it as an initial discovery step, contrasted with using specific tools directly.

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