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parcel_details

Read-onlyIdempotent

Get the full record for one parcel by its account id: address, current assessed value (total, land, improvement), land use, zoning, year built, structure square footage, lot size, coordinates, and most recent sale. Valuation and characteristics only, no owner name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNo2-letter state code. Coverage: 'MD' (Maryland statewide) or 'TX' (Harris County / Houston only). Defaults to MD.
account_idYesParcel account id (from parcel_search).

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description's burden is lower. The description adds meaningful behavioral scope: it returns valuation and characteristics only, excludes owner names, and limits sale data to the most recent sale rather than full history. It does not discuss nulls or missing fields, but that is minor for this use case.

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?

One dense, front-loaded sentence that states the action, resource, key, and a complete field list. There is no repetition or filler; every phrase carries signal.

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 full schema coverage and safety annotations, nothing critical is missing: the id source is referenced in the schema, default/coverage behavior is documented, return fields are enumerated, and the owner-name exclusion prevents misuse. The absence of an output schema is mitigated by the explicit field list in the description.

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%, with both state and account_id already documented clearly. The description does not add parameter-level detail beyond the schema, so the baseline of 3 applies.

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 ('Get') and names the exact resource ('full record for one parcel') keyed by account id. It enumerates the returned fields, and explicitly distinguishes itself from owner- or history-focused siblings by noting 'Valuation and characteristics only, no owner name.'

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 usage context is clear: call it when you need a comprehensive single-parcel record by account id. It does not explicitly name alternatives like parcel_search or parcel_sales_history, but the owner-name exclusion and 'most recent sale' wording implicitly delimit when this tool is or is not appropriate.

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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