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LiveDataLink

by io.github.blackboxfoundry

recreation_search_recareas

Read-onlyIdempotent

Search federal recreation AREAS (broader units: a whole national forest, a national park unit, a BLM management area) by name, state, or activity. For higher-level place search use this; for specific facilities (campgrounds, trailheads) use recreation_search_facilities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows (1-50, default 10).
queryNoFree-text match on recreation-area name.
stateNoTwo-letter state code.
activityNoActivity name.

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the federal scope and broad-unit interpretation of 'areas,' but it does not disclose additional behavioral details such as result shape, pagination beyond the schema, or empty-query behavior.

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 with no filler. The purpose and scope are front-loaded, and the second sentence earns its place by routing to the correct sibling with concrete examples.

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

Completeness5/5

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

For a simple search tool with all parameters documented, rich read-only/idempotent annotations, and no required parameters, the description is complete enough for an agent to call it correctly. It provides scope, filter dimensions, and sibling guidance in a compact form.

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?

All four parameters have schema descriptions, giving 100% coverage, so the baseline applies. The description adds only the grouping phrase 'by name, state, or activity,' which maps to query, state, and activity but introduces no new format or constraint details beyond the schema.

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?

The description states an unambiguous action: search federal recreation areas by name, state, or activity, and defines 'areas' as broad units such as national forests or park units. It also explicitly contrasts itself with recreation_search_facilities, distinguishing it from the closest sibling.

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

Usage Guidelines5/5

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

The description directly instructs when to use this tool ('For higher-level place search use this') and names the alternative for specific facilities. It even gives concrete examples like campgrounds and trailheads, leaving no ambiguity about which sibling to prefer.

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

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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