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LiveDataLink

by io.github.blackboxfoundry

property_search_owner

Read-onlyIdempotent

Filter the bounded Montgomery County, TX demo property records by a supplied owner-name query. Partial matching is supported, but owner names are not returned. Matching results include addresses, values, property types, and account numbers for the sample records. This is not an owner-verification or people-finder service. Coverage note: the current Montgomery County, TX connector returns demo/sample records only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countyNoCounty name (default: montgomery)montgomery
owner_nameYesFull or partial owner name to search for

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotation safety profile, the description discloses concrete behavioral traits: partial matching is supported, owner names are not returned, matching results only include addresses/values/property types/account numbers, and data is demo/sample only. This meaningfully sets expectations for an agent calling the tool.

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?

Every sentence adds value: scope, matching behavior, returned fields, non-purpose, and data-coverage caveat. It is compact, front-loaded with the core action, and contains no redundancy or filler.

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 two-parameter read-only tool with no output schema, the description covers input semantics, output fields, limitations, and exclusions. Nothing essential for correctly selecting or invoking this tool is missing.

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 description coverage is 100%, so the schema already documents both parameters ('county' default and 'owner_name' semantics). The description reinforces that partial owner-name matching is supported but does not add materially new parameter-level detail 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 names a specific verb ('Filter'), a precise resource ('bounded Montgomery County, TX demo property records'), and an explicit query dimension ('owner-name query'). It also delists what results include and explicitly disclaims owner-verification/people-finder scope, so an agent can tell it apart from broader people-search or property-area tools.

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 makes the intended use clear: filter demo property records by owner name. It also gives a clear when-not ('This is not an owner-verification or people-finder service') and a coverage caveat ('demo/sample records only'), though it does not explicitly name alternative sibling tools for area-based or parcel-based property searches.

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.

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