USGS official earthquake summary feed by period and minimum magnitude. period: hour|day|week|month. min_mag: 1.0|2.5|4.5|significant. Returns all events worldwide above the threshold within the period, with magnitude, location, depth, and event detail URL.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Time window (default 'day') | |
| min_mag | No | Minimum magnitude threshold (default '2.5') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds useful context by noting it returns all events worldwide and lists the returned fields, but it does not address formats, pagination, rate limits, or ordering. This is adequate but not rich beyond the annotation baseline.
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 compact, front-loaded with the tool's purpose, and structured logically: what it is, the two parameters, then the return contents. The parameter list partially duplicates the schema but does not add meaningful length or confusion.
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 two-parameter read-only feed with rich annotations, the description is nearly complete: it specifies the period options, magnitude thresholds, worldwide scope, and returned fields. It omits potential details like pagination or response format, but those are not essential for an agent to correctly select and invoke this tool.
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% and both parameters already have enum definitions and default descriptions. The description restates the enum values ('hour|day|week|month' and '1.0|2.5|4.5|significant') without adding meaning beyond the schema. Per the baseline for high schema coverage, this is a solid 3.
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 uses a specific verb ('Returns') and identifies the exact resource: a USGS earthquake summary feed filtered by period and minimum magnitude. It clearly states what events come back and which fields are included. It does not explicitly contrast itself with sibling tools like usgs_earthquake_search or usgs_earthquake_detail, though the 'feed' framing implies a broad period-based view.
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: fetch all worldwide earthquakes within a time window above a magnitude threshold. However, it provides no explicit guidance on when to choose this tool over siblings such as usgs_earthquake_search, usgs_earthquake_detail, or earthquake_recent, nor does it state 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.
Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.
The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.
290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.
For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.