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

Annotations already establish readOnlyHint=true and openWorldHint=false, so the description has a lower bar. It still adds genuinely useful behavior context: the score is computed by a transparent database query with "No model call", so the agent knows results are deterministic and explainable rather than LLM-generated. It stops short of describing ordering, tie-breaking, or what the explanation text looks like.

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?

Two sentences, zero filler, and the core action plus the key differentiator (transparent, non-model score) are front-loaded. Nothing in the description is repeated from the title or wasted.

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?

With 11 parameters and only one required, the description never says the remaining ten are optional profile filters that refine the match, nor what happens when they are omitted (broad match? lower score confidence?). Since there is no output schema, the description carries some return-value burden and does say scores are explained, but the shape of the result (ranked list with per-item rationale) is only implied.

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% with four enums, so all 11 parameters are already documented in structured form; the description adds no parameter-level meaning beyond what the schema says. Baseline 3 applies. One gap the description could have closed but did not: which of the ten optional filters meaningfully change the ranking versus merely narrow candidates.

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?

"Ranks the open calls for a business profile and explains each score" gives a specific verb (ranks), resource (open calls/bandi) and output characteristic (explained scores). It does not name or contrast itself with search_incentives, the obvious sibling, so the agent must infer the distinction between profile-based ranking and keyword search.

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?

Use is implied: an agent that has a set of business attributes (region, size, sector, purposes) will infer this is the profile-matching path, and the word "Ranks" hints results are ordered rather than filtered. However, there is no explicit "use this instead of search_incentives when..." routing and no statement about which parameters actually affect the score.

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