List federal recreation facilities within a radius of a coordinate. Useful for proximity searches (e.g. campgrounds near a property, fishing spots near a city). Radius is in kilometers.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Center latitude. | |
| lon | Yes | Center longitude. | |
| limit | No | Max rows (1-50, default 10). | |
| activity | No | Optional activity filter. | |
| radius_km | No | Radius in kilometers (default 30, max ~320). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only, idempotent, non-destructive behavior, lowering the burden on the description. The description adds the geographic scope and radius unit but does not disclose return format, pagination, or open-world result behavior. This is adequate but adds limited behavioral detail beyond the annotations.
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?
Three short sentences front-load the core action, then provide useful examples and the key unit caveat. There is no filler and only minor overlap with the schema's radius description.
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?
The tool is a simple read-only proximity list with all input parameters documented in the schema; the description supplies enough selection context for an agent. Without an output schema, mentioning what the returned facilities look like would improve completeness, but the low complexity and strong annotations make the definition sufficient.
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 covers 100% of parameters with descriptions, so the baseline is 3. The description's only parameter-related addition is stating that radius is in kilometers, which is already in the schema's radius_km description. It does not meaningfully enrich parameter semantics beyond the schema.
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 states a specific action and object: list federal recreation facilities within a radius of a coordinate. It is clear what the tool does, including that it is a geospatial proximity search. It does not explicitly differentiate from near-named siblings like recreation_search_facilities, so it stops short of a 5.
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 phrase 'Useful for proximity searches' with concrete examples (campgrounds near a property, fishing spots near a city) provides clear context for when to use the tool. It does not name alternatives or exclusions, so it lacks the explicit routing of a 5.
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.