OpenAQ air quality — PM2.5/PM10/NO2/O3 by city/country, lastUpdated. v3 API + v2 fallback. Env / health / geo pulse. For PM market disclaimers.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max locations, default 30 | |
| country | No | ISO country code e.g. US |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description must carry the behavioral burden. It mentions API version and fallback, but does not explicitly state the tool is read-only, whether authentication is required, or rate limits. The read-only nature is implied but not confirmed.
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?
Description is concise but includes unclear phrases like 'Env / health / geo pulse' and 'For PM market disclaimers' that may confuse agents. A clearer structure identifying output would improve it.
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 no output schema, description should hint at return structure. It mentions 'lastUpdated' but not other fields or format. For a simple tool, it is adequate but leaves gaps about what the agent can expect.
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?
Schema coverage is 100%, both parameters have descriptions. Description adds context about filtering by city/country but does not add significant meaning beyond the schema. Baseline 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?
Description clearly states the tool retrieves air quality data (PM2.5/PM10/NO2/O3) by city/country with lastUpdated field, and specifies API version. However, it does not distinguish from sibling tool 'air_quality_index' despite being in a similar domain.
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?
No guidance on when to use this tool versus alternatives. Does not mention scenarios where air_quality_index or other weather tools might be more appropriate.
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.
Tools cover very diverse domains (weather, FDA, legal, crypto, etc.), so cross-domain confusion is low. However, within domains there is notable overlap: multiple food recall tools (food_recall_check, food_safety), multiple weather tools (weather_current_global, weather_forecast_grid, weather_alerts, weather_bias), and several Polymarket-related tools. This can cause agent misselection.
Naming is inconsistent: some tools use verb_noun (search_arxiv, scrape, validate_agent_manifest), others use noun phrases (smart_money, space_weather, tide_data), and some are long descriptive phrases (cross_platform_arb_scan, polymarket_event_scan). No single pattern is followed, making predictions difficult.
95 tools is excessively high for any coherent purpose. The server appears to be a random aggregation of APIs with no clear scope. Such a large catalog overwhelms agents and dilutes utility; most tools could be split into specialized servers.
Although many domains are touched, each is covered only shallowly. For example, weather lacks historical data, legal lacks case details beyond court opinions, and financial lacks stock prices. There are obvious gaps like no user authentication or data persistence. The tool set feels like a collection of endpoints rather than a cohesive service.