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

With no annotations supplied, the description does meaningful work: it names the corpus and its subject matter, discloses the return shape (a list of results with ids), and points to the follow-up call. It does not mention ranking behaviour, pagination, or whether the search is read-only, which leaves some burden unmet for a zero-annotation tool.

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 corpus definition and the fetch hand-off are front-loaded, so the essential facts come first. The full bilingual duplication doubles the length, which is defensible for localisation but is still redundant text for a single reader.

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 four-parameter read tool with a fully documented schema and no output schema, the description covers the corpus, the result shape, and the next step, which is enough to call it correctly. The remaining gap is operational detail such as ordering or paging, which matters only at larger result sizes.

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%, so the baseline is 3. The description does add real meaning by explaining what each 'site' value covers topically (private AI vs. fibre/networks/data centres), which helps the agent choose a site filter, but it says nothing about 'limit' or 'language' beyond what the schema already documents.

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 (searches) plus the exact corpora searched: csidia.com operational notes (private AI, open-weight models, compliance) and splidia.com (optical fibre, networks, data centres). It also distinguishes itself from the sibling 'fetch' by saying results carry ids to be passed there, so an agent can tell the two apart without opening a schema.

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?

Clear context for use: keyword search across the two sites, followed by 'fetch' on returned ids, which establishes the intended two-step workflow. It gives no explicit when-not-to-use guidance, though — nothing tells the agent when 'match_use_case' or 'capabilities' would be the better choice.

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