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

Goes well beyond the readOnlyHint/openWorldHint annotations by disclosing the cost ('1 credit per call'), the ranked nature of results, and the deliberate no-silent-disambiguation behavior ('Paris' returns all 20 arrondissements). These are exactly the traits an agent needs before invoking it in a chain.

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-loads purpose, then usage, then behavior and cost in three tight paragraphs. The example strings are repeated from the parameter schema, a minor redundancy, but nothing else is 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 no output schema, the description carries the burden of describing returns and does so ('ranked canonical commune, postal-code, department and INSEE filters'). Combined with cost and disambiguation behavior, an agent has everything needed to call and chain it correctly.

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% and the single parameter is fully documented, so the baseline is 3. The description adds meaning by enumerating accepted input forms (postal codes, communes, arrondissements) and accented/abbreviated variants like 'st etienne', which the enum-less schema cannot express.

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 (resolve), a precise input domain (free-form French administrative locations) and the output (canonical Normi filters). It is clearly distinguishable from all siblings, which are analysis/market tools rather than a geocoding normalizer.

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?

Explicitly says to 'use this before another Normi tool when the location is informal, accented, abbreviated, or ambiguous', giving both the trigger condition and its role as a prerequisite step. No alternative tool competes for this job, so no exclusions are needed.

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