Crédit d'impôt 244 quater W DOM : taux 38.25%, rétrocession 52.63%, formulaire 2069-RCI, cas pratiques. Prix : 0.100 USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| payment_tx_hash | No | Hash tx USDC Base. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the price (0.100 USDC), which is relevant behavioral context not captured by the readOnlyHint annotation. However, it does not clarify whether payment is mandatory for full output, what happens without a valid hash, or any other operational behavior.
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 description is very brief and informative: a short phrase listing the key facts (rates, form, cases) and the price. Every element has purpose, and it's well-structured for quick scanning.
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?
The tool has one parameter, no output schema, and read-only annotation. The description gives a snapshot of the content but omits what the user actually receives (e.g., a document, data fields) and the payment workflow. It's sufficient for a simple, narrowly-scoped tool but leaves gaps around expected output.
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?
The schema describes payment_tx_hash as 'Hash tx USDC Base.' The description adds the cost amount (0.100 USDC), tying the parameter to the payment requirement. This goes beyond the schema's minimal description, though it still doesn't explicitly connect the hash to the payment.
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?
The description clearly identifies the resource: the 244 quater W DOM tax credit, with specific rates and form reference. However, it lacks an explicit action verb (e.g., 'returns' or 'provides'), so it reads more as a content summary than a functional description.
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?
No guidance is given on when to use this tool or how it differs from the many sibling caribbean_get_* tools. There is no mention of alternatives or exclusions, leaving the agent to infer usage solely from the name and topic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools have clearly distinct domains (solar, biodiversity, water, etc.), but the pair caribbean_get_marches_publics and caribbean_get_marches_publics_dom overlap significantly, differing only in geographic scope. The sub-group of 'caye' tools (marche, vanille, vetiver) are also thematically similar, though descriptions clarify their specific commodities. Overall, an agent could generally select correctly, but a few boundary cases exist.
The tools overwhelmingly follow a caribbean_get_<subject> convention, with only two exceptions: caribbean_analyse_solaire (uses 'analyse' instead of 'get') and caribbean_list_marketplace (uses 'list' instead of 'get'). This makes the pattern predictable and readable, with minor deviations that are still intuitive. The subject names are consistently descriptive, though some use abbreviations like 'dom' and 'oa' that might require context.
24 tools is on the heavy side for a single server, particularly given that many tools are single-purpose data lookups (e.g., biodiversity, eDNA, tourism). The count is justifiable for a wide-ranging Caribbean data API, but it risks overwhelming an agent with a large surface. It is not excessive enough to be absurd, but it's in the 'heavy' zone.
The server covers multiple domains comprehensively, such as solar energy (tariffs, irradiation, connection, tax credit, financing) and public contracts (Guadeloupe and all DOM). The marketplace meta-tools (llms_txt, list_marketplace, get_provider) ensure discoverability, but there is no general search or aggregation tool. Some areas like agriculture or real estate beyond what's present could be considered gaps, but the core coverage is solid.