Air-quality snapshot (PM2.5, PM10, US / European AQI and a coarse category) for a lat/lon via the free Open-Meteo air-quality API. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude (-90..90) | |
| lon | Yes | Longitude (-180..180) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by stating 'Read-only; price 0.0 (free)'. This discloses that the tool is safe (no mutations) and has no cost. However, it could add more details like rate limits or source freshness.
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 a single sentence that directly states the tool's purpose, key outputs, and essential traits (read-only, free). Every element contributes uniquely, and it is front-loaded with the primary action.
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?
Given the simplicity (2 params, no output schema), the description adequately informs an agent about what the tool returns and its safety profile. It could mention that the snapshot is for current conditions, though 'snapshot' implies that. No output schema exists, so completeness is high but not perfect.
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 covers both parameters (lat, lon) with descriptions. The description merely mentions 'for a lat/lon', adding no extra semantic value or usage hints beyond what the schema provides. Since schema coverage is 100%, 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 specifies the tool provides an 'Air-quality snapshot' including specific pollutants (PM2.5, PM10), both US and European AQI, and a coarse category, for a given lat/lon. This clearly distinguishes it from sibling weather tools like weather_risk_current_weather or weather_risk_forecast, which focus on different aspects.
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 implies usage for air quality queries via the Open-Meteo API, but it does not explicitly state when to use this tool over alternatives (e.g., for current vs. forecast air quality) or mention prerequisites or limitations like data freshness.
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, especially the ledger-watch groups with domain prefixes. However, there are near-duplicate utilities such as content_authenticity_domain_reputation and domain_intel_reputation, and fx_tax_convert overlaps with price_oracle_fx_rate/convert. The sheer number of tools also increases the chance of selecting the wrong one, though descriptions are generally clear.
The naming is largely consistent with a <domain>_<action> or <domain>_<watch>_<action> pattern, and all names use snake_case. Minor deviations include standalone names like entity_search, kyb_report, verify_receipt, and the confusing singular/plural pair of sanction_watch_* and sanctions_screen_*. Overall, the pattern is predictable.
With 172 tools, this server is far beyond the typical well-scoped range. It bundles dozens of unrelated utility domains (weather, carbon, CVE, geo, etc.) alongside the Japan public-ledger watches, making it unwieldy for an agent to navigate. This extreme count is a major coherence problem.
For the core Japan public-ledger domain, coverage is excellent: each ledger has search, get, timeline, recent_changes, and verify_ledger, plus cross-ledger entity_search and temporal_query. The unrelated utility areas are also fairly complete for their own purposes, but the server's scope is so broad that some utilities are duplicated (e.g., multiple currency converters). Overall, no critical dead ends in the main domain.