Tarifs EDF OA pour l'énergie solaire en ZNI (971, 972, 974, 976). Contrats 20 ans. 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?
Despite the readOnlyHint annotation, the description adds no behavioral context. It fails to disclose that the tool may return either payment instructions (when no payment_tx_hash is provided) or actual tariff data, nor does it explain response format or any dependence on payment state. The domain facts (20-year contracts, 0.020 USDC) are not behavioral.
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 extremely concise and front-loaded, using three short fragments to convey the core subject, scope, and key pricing details. Every sentence earns its place with no redundant wording.
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 and a payment-dependent behavior, the description is incomplete. It does not explain what the response contains in either case (payment instructions vs tariff rates), nor how the payment hash affects execution. A user would not know what to expect or how to proceed.
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 payment_tx_hash with a clear description (hash format and behavior when absent), achieving 100% schema coverage. The tool description adds nothing about the parameter beyond what the schema provides, so it stays at the baseline.
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 provides EDF OA feed-in tariffs for solar energy in specific ZNI regions (971, 972, 974, 976), with contract length and price. This specific verb+resource+scope distinguishes it from sibling tools like caribbean_get_irradiation_dom or caribbean_get_raccordement.
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 gives no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or related tools. The only implied usage is 'when you need these tariffs,' but there is no explicit contextual instruction.
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.