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LiveDataLink

by io.github.blackboxfoundry

nonprofit_search_location

Read-onlyIdempotent

Find tax-exempt organizations by location: city, state, and/or 5-digit ZIP. At least one filter is required. Useful for discovering charities, churches, and foundations in an area. Returns up to 100 organizations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNo5-digit ZIP code.
cityNoCity name (combine with state for best results).
limitNoMax results to return (default 20, max 100).
stateNo2-letter US state/territory code, e.g. "TX".

TDQS

A4.2/5.0
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 useful behavior: the required-filter constraint and the 'up to 100 organizations' result cap, but it does not disclose return format or potential empty-result 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?

Three short sentences convey the resource, the location filters, the required-filter constraint, the use case, and the result cap. There is no filler or duplication of schema details.

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 simple read-only search tool with full parameter schema coverage, the description covers the essential invocation rule and result limit. It would be slightly stronger if it indicated the shape of the returned organization records or explicitly contrasted with name/EIN-based sibling tools.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents each parameter. The description adds important cross-parameter semantics that the schema cannot express: at least one of city/state/ZIP is required even though all properties are individually optional. It also clarifies the limit cap.

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 uses a specific verb ('Find'), names the resource ('tax-exempt organizations'), and clearly identifies the search axis ('by location: city, state, and/or 5-digit ZIP'). This differentiates it from sibling tools like nonprofit_lookup_ein and nonprofit_search_name, which are identifier- or name-based.

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

Usage Guidelines4/5

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

The description gives clear usage context: it is for discovering organizations in an area and explicitly states that at least one filter is required. However, it does not explicitly mention alternatives or when not to use this tool, leaving some routing to inference.

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