Live conditions at a Puerto Rico spot from public data (Open-Meteo): wave height/period/direction, sea-surface temp, air temp, and wind. Use list_condition_spots for valid keys.
| Name | Required | Description | Default |
|---|---|---|---|
| spot | Yes | Spot key, e.g. 'rincon' (see list_condition_spots) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that data comes from public API (Open-Meteo) and warns about using valid keys via list_condition_spots, which are useful behavioral traits. It does not mention update frequency or error handling, but for a read-only conditions tool, this is adequate.
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 purpose, and includes only essential details without redundancy. Every phrase adds 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 simple one-parameter read tool with no output schema, the description is complete: it lists all data fields, names the data source, and tells the agent where to find valid keys. No critical information is missing for correct invocation.
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 already describes the 'spot' parameter with an example and reference to list_condition_spots, so the description adds no new information. Since schema coverage is 100%, the baseline of 3 is appropriate.
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's function: retrieving live marine and weather conditions (wave height/period/direction, sea-surface temp, air temp, wind) for a Puerto Rico spot. It specifies the data source (Open-Meteo) and distinguishes from sibling tools like get_town_weather by focusing on surf/beach conditions.
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 clear usage context: use this tool for live spot conditions, and points to list_condition_spots for valid keys. However, it does not explicitly say when not to use it or compare with other siblings like get_town_weather, so it lacks explicit exclusions.
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 purposes: ask synthesizes answers, search_news does semantic retrieval, keyword_search_news does keyword matching, and the get_/list_ tools target specific data types. However, search_pr_news is a redundant alias, and get_by_entity vs get_by_municipality overlap on place queries, creating minor ambiguity.
Tool names use a mix of prefixes (get_, list_, search_) and include a bare verb (ask), which is not fully consistent. The legacy alias search_pr_news further deviates from the pattern, though the rest are readable and predictable.
With 13 tools spanning news, Q&A, weather, cost-of-living, and safety, the count fits the server's broad purpose without being excessive. Each major domain has dedicated tools, and despite one redundant alias, the set remains well-scoped.
The tool set covers article discovery, synthesis, weather, demographics, and safety statistics, providing solid domain coverage. Minor gaps include no full-text article retrieval and no dedicated section browsing, but summaries and links make these workable.