USGS all-day earthquakes — mag, place, time, tsunami, felt, coords, depth. Public USGS GeoJSON no-key. Disaster / insurance / commodity market tail-risk pulse.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max quakes, default 50 | |
| min_mag | No | Min magnitude e.g. 2.5 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description bears full burden. It notes the tool is public and requires no API key, but does not disclose other behavioral traits like data freshness, rate limits, or what happens when no earthquakes match criteria. Minimal behavioral context beyond basic data source.
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 concise, using a dash-separated list and tags. It is front-loaded with key information, but the structure is somewhat fragmented and could be improved with clearer sentence flow. Still efficient.
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, the description hints at the return format by mentioning 'USGS GeoJSON' and listing fields, but does not explicitly describe the output structure or pagination. It is adequate for a simple data retrieval tool but leaves gaps for agents unfamiliar with USGS APIs.
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 in the schema). The description does not add extra meaning beyond what the schema provides; it mentions magnitude in the output but not parameter specifics. Baseline 3 is appropriate, no additional value.
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 it retrieves USGS earthquake data, listing key fields (mag, place, time, etc.) and the data source (USGS GeoJSON). It also distinguishes from siblings by focusing specifically on earthquakes, with no directly similar sibling tool.
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 use for earthquake data and mentions tail-risk pulse for disaster/insurance/commodity contexts, but does not explicitly specify when to use this tool versus alternatives or provide exclusions. Context is clear but lacks guidance on when not to use it.
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.