Intelligence économique Guadeloupe : 42 000 entreprises, 6 secteurs clés (BTP, ENR, agriculture, services), profils TPE/PME, points de douleur, réseaux CCI/BPI. Prix : 0.050 USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| payment_tx_hash | No | Hash tx USDC Base (0x+64hex). Absent = instructions paiement. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a price ('Prix : 0.050 USDC'), which is a meaningful behavioral trait beyond the readOnlyHint annotation. It also implies a payment requirement via the transaction hash parameter, adding valuable context that this is a paid data access tool. However, it does not detail the payment workflow or response behavior when payment is absent.
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 a single sentence that efficiently lists key data points and the price. It is front-loaded with the subject and contains no filler. But it is more of a data catalog summary than a clear functional description, slightly reducing structure value.
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 tool with one optional parameter and no output schema, the description gives a decent overview of the data content and cost. However, it does not explicitly state what the tool does or how the payment flow works, relying on the schema's param description. This is adequate but has gaps.
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 input schema already documents the parameter fully (hash format and 'Absent = instructions paiement'), and schema coverage is 100%. The description adds only the price, which is related but not extra parameter syntax or semantics. Baseline of 3 applies because the schema carries the parameter detail.
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 is a noun phrase ('Intelligence économique Guadeloupe') followed by a content list, but it does not state the tool's action. There is no verb like 'get' or 'retrieve'; the only verb is in the tool name, not the description. This makes the tool's purpose ambiguous beyond what the name implies.
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 a use case through its content (economic intelligence on Guadeloupe's SMEs), but it gives no explicit guidance on when to use this tool versus alternatives. Sibling tools cover different Caribbean topics, yet the description does not contrast with them or mention conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.