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

Annotations already declare readOnly/idempotent/non-open-world, and the description adds substantial extra context: the hybrid lexical+semantic ranking method, that sponsorship never affects ranking, that confidence is always UNKNOWN because records are non-attested publisher facts, and that results are never padded. This is exactly the kind of behavioral disclosure annotations cannot carry.

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 the verb and resource in the first clause, and the later sentences on ranking, confidence and NO_MATCH all carry real information. It is a dense single paragraph, though, and the ranking-method detail (Cloudflare Workers AI embeddings) is more implementation trivia than agent-facing guidance.

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?

Even though an output schema exists, the description explains the response shape (request_id, status, options with id/label/description/provenance) and the meaning of the NO_MATCH state, which is what an agent actually needs to interpret results. Nothing material is missing for a 4-parameter, read-only search tool.

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 baseline is 3, but the description adds value: it gives concrete example needs and confirms the English/French language support that drives the `lang` parameter, and ties the catalogue's business-process organisation to the optional `process` filter. It stops short of elaborating the process enum values themselves, which the schema handles.

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 resource (HODDS catalogue of software, SaaS, APIs and online services), the accepted input form (English or French need) and gives concrete example queries. An agent can distinguish this discovery tool from siblings like get_solution, compare_solutions or find_comparable_solutions without opening any 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?

The description implies this is the entry-point discovery tool and explains the terminal NO_MATCH status, but never explicitly says when to use it instead of compare_solutions, get_solution or list_processes. The only exclusions given are about results (no padding, no match) rather than about tool selection.

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