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

No annotations are supplied, so the description carries the burden, and it does add real context: the current corpus size (1,961 fiches) and freshness date, plus why RUP status matters (75% vs 66% donor deduction, credibility signal). 'List' clearly implies a read-only, non-mutating operation. It does not describe return fields, ordering, or how filters combine, which keeps it below 5.

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?

Three sentences, front-loaded with the defining scope, then freshness, then use cases. Every sentence contributes domain value. The tax-deduction detail is slightly tangential for a listing tool but still helps the agent justify selection, so it earns its place.

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-optional-parameter listing tool with no annotations and no output schema, the description supplies the key missing context: what the corpus is, how large and fresh it is, and why it is a distinct dataset. It leaves the shape of returned fiches unstated, which is a minor gap since no output schema exists to cover it.

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 all four parameters (limit, query, region, department) are already documented with examples and defaults. The description adds no additional meaning about how filters interact or what 'fiche' contents look like. Baseline 3 applies when the schema does the heavy lifting.

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 ('List') and a precisely scoped resource ('associations officially recognized as utilite publique (RUP) by French state decree'). The RUP qualifier is a hard domain filter that separates it from generic siblings like search_associations or get_health_associations without needing to name them.

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?

Gives an explicit use context: 'Recommended for institutional grounding -- mecenat, defiscalisation, public-private partnerships, B2B research.' That tells the agent when to reach for this tool. It stops short of naming alternatives or stating when NOT to use it (e.g. when generic association search is wanted), so it falls short of a 5.

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