Currently-active National Weather Service alerts (tornado, flood, severe thunderstorm, winter, heat, fire) for a point, state, or NWS zone.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | ||
| lon | No | ||
| zone | No | NWS zone id, e.g. 'TXZ123'. | |
| state | No | Two-letter state code (e.g. 'TX'). | |
| location | No | Address, zip, or city. Will be geocoded to a point. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already cover the safety profile with readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to restate those. It adds useful temporal scoping ('currently-active') and alert categories, but does not describe output shape, no-alert behavior, or geocoding failure handling, and there is no output schema to compensate.
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?
A single front-loaded sentence with no redundant words. It efficiently conveys the resource, alert types, and location modes.
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 read-only lookup with no required parameters, the description is nearly sufficient: an agent can infer the tool's purpose and choose a location input. The main omissions are return-format details and explicit guidance on parameter mutual exclusivity, but these are not blockers for invoking the 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?
The schema already documents zone, state, and location, while lat/lon are only named. The description adds the conceptual grouping 'point, state, or NWS zone,' but does not clarify whether these are mutually exclusive options or that lat/lon must be supplied together, so parameter semantics are adequate but incomplete.
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 identifies the resource (currently-active NWS alerts), lists representative alert categories, and specifies the supported selectors (point, state, NWS zone), making it distinguishable from weather_current and weather_forecast. It stops short of a 5 because it is phrased as a noun phrase rather than an explicit verb like 'list' or 'retrieve'.
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 application context: use for currently active NWS alerts at a point, state, or zone. It does not explicitly contrast with sibling weather tools or state exclusions such as 'for conditions or forecasts, use weather_current/weather_forecast instead,' so it lacks full alternative guidance.
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.