Vétiver caribéen parfumerie luxe : prix vs Haïti vs Inde, profil olfactif, potentiel Guadeloupe. Prix : 0.050 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?
Beyond the readOnlyHint annotation, the description discloses a cost of 0.050 USDC, which is a behavioral trait. However, it does not explain how the cost is applied, whether payment is mandatory, or what the payment_tx_hash parameter is for, leaving the payment behavior ambiguous. Still, it adds some useful context beyond the annotation.
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 every word carries information, making it concise. However, it is fragmented, using keyword-style phrases rather than a clear, structured sentence, which slightly reduces clarity.
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 appears to be a paid data service, but the description does not clarify what the output will be (e.g., a report, data table, or text), whether payment is required to access the data, or how the payment_tx_hash parameter is used. With no output schema and no further details, the description leaves significant gaps for a tool that may require payment.
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 payment_tx_hash as 'Hash tx USDC Base' (100% coverage), so the baseline is 3. The description mentions the price but does not explicitly link it to the parameter or add any additional 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 identifies the tool's focus: Caribbean vetiver luxury perfumery, with specific elements (price comparison between Haiti and India, olfactory profile, Guadeloupe potential). This distinguishes it from sibling tools like caribbean_get_caye_vanille (vanilla) and caribbean_get_biodiversite, and the 'get' verb in the tool name is reinforced by the concrete data points listed.
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?
There is no guidance on when to use this tool versus alternatives, no mention of prerequisites, and no exclusions. The price note ('Prix: 0.050 USDC') is not a usage guideline and does not explain the conditions for using the 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.