Accède aux données d'un fournisseur tiers de la marketplace. Utiliser caribbean_list_marketplace d'abord pour connaître les slugs disponibles. Commission 25% incluse dans le prix.
| Name | Required | Description | Default |
|---|---|---|---|
| endpoint_slug | Yes | Slug endpoint (ex: filieres-banane) | |
| provider_slug | Yes | Slug fournisseur (ex: agri-guadeloupe) | |
| payment_tx_hash | No | Hash tx USDC Base. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the bar is lower. The description adds the commission-inclusive pricing detail and third-party data source context, but does not disclose potential rate limits, auth requirements, or return behavior. This is modest added value beyond annotations.
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 two sentences, front-loaded with the core action, and every clause earns its place. It is succinct without sacrificing essential usage guidance.
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 generic getter with well-documented schema and annotations, the description covers the main usage prerequisite (list first) and a key business rule (commission). It does not describe return shape, but no output schema exists and the tool's purpose is fairly simple. Minor omissions like optional payment_tx_hash context are acceptable.
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 the schema fully documents all three parameters with examples. The description reinforces the concept of 'slugs' but adds no new parameter-level meaning beyond what the schema already provides.
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 states the tool accesses data from a third-party marketplace provider, using a specific verb and resource. It differentiates itself from siblings by being a generic marketplace getter, though the exact nature of 'marketplace' isn't elaborated. The mention of commission adds specificity.
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 instructs to use caribbean_list_marketplace first to discover available slugs, establishing a clear prerequisite. This is strong usage guidance that also implicitly distinguishes when to use this tool versus the listing tool.
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.