Skip to main content
Glama

recreation_search_facilities

Read-onlyIdempotent

Search US federal recreation facilities (campgrounds, picnic areas, trailheads, marinas, visitor centers) across NPS, USFS, BLM, USACE, BOR, FWS. Filter by name, state, or activity (e.g. 'CAMPING', 'FISHING', 'HIKING').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows (1-50, default 10).
queryNoFree-text match on facility name.
stateNoTwo-letter state code, e.g. 'CA'.
activityNoActivity name (CAMPING, FISHING, HIKING, etc.).

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the description carries a lower behavioral burden. It adds agency/facility-type scoping context but discloses no additional behavioral traits such as pagination, result count, or output shape. Nothing contradicts 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the action verb, and zero filler. The first sentence covers what is searched and across which agencies; the second covers all filter dimensions; every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only search tool, the description plus 100%-covered schema and rich annotations together supply what an agent needs to invoke it correctly. The only notable omissions are explicit sibling routing and an undocumented return shape, though no output schema exists to compensate for the latter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and every parameter (limit, query, state, activity) already has a clear description, so the baseline is 3. The tool description adds marginal value by citing concrete activity examples (CAMPING, FISHING, HIKING) that reinforce the schema's 'etc.', but introduces no new semantic information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource ('Search US federal recreation facilities') and enumerates both facility types (campgrounds, picnic areas, trailheads, marinas, visitor centers) and managing agencies (NPS, USFS, BLM, USACE, BOR, FWS), making the scope unmistakable. The breadth of the search also implicitly distinguishes it from the campsite- and rec-area-specific sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by listing facility types and filter dimensions, but never states when to prefer this tool over recreation_search_campsites, recreation_search_recareas, or recreation_facility_detail. With four recreation siblings present, the absence of explicit when-to-use or when-not-to guidance is a real gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.2/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count1/5

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.

Completeness4/5

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.

Resources