Irradiation solaire DOM par commune : GHI + PVOUT (Guadeloupe, Martinique, La Réunion, Mayotte). Données NASA POWER + Solargis. Formule production kWh/an incluse. Prix : 0.020 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 readOnlyHint annotation is consistent with the read-only nature. The description adds valuable context beyond the annotation by specifying data sources (NASA POWER + Solargis), the inclusion of a kWh/year formula, and the price (0.020 USDC). No contradiction.
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?
Two concise sentences deliver the core purpose, scope, data sources, formula, and price. Front-loaded and free of fluff.
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 description covers dataset scope, regions, data sources, formula, and price. With no output schema, a bit more detail on the return format could help, but for a simple data retrieval tool with one optional parameter, it is adequately complete.
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 fully describes the single optional parameter (payment_tx_hash) with 100% coverage, including the behavior if absent. The description does not add parameter semantics but does not need to since the schema is complete.
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 explicitly states the tool provides solar irradiation (GHI + PVOUT) for French overseas departments, lists the specific regions (Guadeloupe, Martinique, La Réunion, Mayotte), and mentions data sources. This clearly distinguishes it from sibling tools that cover other datasets.
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 provides clear context: this is the tool for solar irradiation data in DOM communes, with data sources and price. It does not explicitly name alternatives or exclusions, but the sibling tools are all distinct topics, so usage is effectively clear.
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.