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LiveDataLink

by io.github.blackboxfoundry

carrier_vetting_evidence_pack

Read-onlyIdempotent

Produce an auditable Carrier Vetting Pack for a freight broker. Resolve a US motor carrier by USDOT, MC, or legal name, then return the GO/CAUTION/NO-GO verdict, the exact FMCSA authority/insurance/safety evidence, sanctions/court/federal-award checks, source coverage and failures, retrieval timestamp, primary-source links, and a broker follow-up checklist. This is the evidence-first companion to carrier_vetting_score: use it when a human reviewer needs to save or forward the record. It is an analytical aid, not a substitute for direct FMCSA insurance and authority verification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mcNoMC/MX number without the prefix.
dotNoUSDOT number (preferred exact identifier).
nameNoLegal carrier name when DOT/MC is unavailable.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, and the description adds valuable context beyond those: it is auditable, includes source coverage and failures, retrieval timestamp, primary-source links, and a broker follow-up checklist. The 'analytical aid, not a substitute' caveat further clarifies limitations.

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?

The description is dense but every sentence earns its place: it states the deliverable, enumerates the output, gives usage guidance, and adds a safety caveat. It is front-loaded with the core purpose and contains no 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?

Given the tool's complexity and lack of an output schema, the description thoroughly covers what the agent can expect: verdict, FMCSA evidence, sanctions/court/federal-award checks, source coverage/failures, timestamp, links, and a checklist. It is complete enough for an agent to decide when to invoke it and what it will return.

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 mc, dot, and name. The description restates that resolution can happen by 'USDOT, MC, or legal name' but adds little beyond what the schema provides. This meets the baseline but does not elevate it.

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 and resource: 'Produce an auditable Carrier Vetting Pack for a freight broker.' It clearly enumerates the deliverable contents and explicitly distinguishes itself from the sibling carrier_vetting_score as the 'evidence-first companion.'

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 gives explicit when-to-use guidance: 'use it when a human reviewer needs to save or forward the record.' It also names the related alternative (carrier_vetting_score) and adds a caution that it is 'not a substitute for direct FMCSA insurance and authority verification.'

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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