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

No annotations are present, so the description carries the full burden. 'Report' implies a non-mutating read operation and the description discloses the output dimensions, but it does not explicitly promise read-only behavior or describe failure/error cases. For a low-risk statistics tool this is acceptable, though not rich.

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 focused sentence that front-loads the verb and the specific metrics being reported. There is no filler, repetition of the title, or boilerplate, making it efficient and easy to parse.

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 tool with one optional parameter and no output schema, the description clearly enumerates the returned information: document counts, word totals, and last-crawl timestamps per source. Minor gaps exist around what 'source' means and an explicit read-only guarantee, but the overall simplicity means an agent can invoke the tool with confidence.

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%, since the only parameter, dbPath, is already documented as an alternative SQLite path with a default. The tool description adds no additional parameter meaning beyond the schema, so the baseline of 3 applies.

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 names a specific verb ('Report') and concrete output metrics ('document counts, word totals and last-crawl timestamps per source'), so an agent knows exactly what this tool produces. This also distinguishes it from sibling tools like hub_crawl and hub_query, which focus on crawling or querying rather than aggregate statistics.

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 implies that the tool should be used when aggregate counts, totals, or crawl timestamps are needed, but it never explicitly states when to use it versus alternatives. There is no when-not-to-use guidance or routing to sibling tools, so usage context remains only implied.

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