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load_tender_fraud_shield

Read-onlyIdempotent

Screen a carrier before accepting or dispatching a load. Resolves the carrier and combines FMCSA authority, insurance, safety, sanctions, court, and federal-award evidence with the supplied tender context. Flags inactive authority, missing liability evidence, sanctions or litigation findings, broker-only records, and mismatches between the carrier's reported location and the tender contact address. Returns CLEAR, REVIEW, or BLOCK with reasons, source coverage, primary links, and a dispatcher verification checklist. This is an analytical fraud-screening aid, not a substitute for direct FMCSA or insurance verification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mcNoMC/MX number without the prefix.
dotNoUSDOT number (preferred).
nameNoCarrier legal name when DOT/MC is unavailable.
formatNoReport format. Defaults to markdown.
load_idNoOptional internal load/tender identifier to echo in the report.
carrier_addressNoAddress supplied with the tender or onboarding packet, used for a coarse location consistency check.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate a safe, read-only, idempotent operation. The description adds meaningful behavioral context beyond that: it resolves the carrier, combines multiple evidence sources, flags specific risk indicators, and returns CLEAR/REVIEW/BLOCK with reasons, links, and a checklist. It also discloses that it is an analytical aid and not a substitute for direct verification, which is valuable caveat information.

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 three information-dense sentences with no fluff. It front-loads the primary purpose, then summarizes inputs, outputs, and caveats efficiently. Every sentence contributes to understanding the tool's behavior and limitations.

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?

Although there is no output schema, the description fully compensates by enumerating the return elements: disposition, reasons, source coverage, primary links, and a dispatcher verification checklist. Combined with complete parameter documentation and safety annotations, the description provides sufficient context for correct invocation and interpretation.

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 description coverage is 100%, so parameters are already well documented in the schema. The description adds extra semantic value by explaining how the carrier address is used for 'coarse location consistency check' and by framing the tender context as part of the screening logic, which enriches understanding beyond the parameter names alone.

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 opens with a specific verb and resource: 'Screen a carrier before accepting or dispatching a load.' It clearly defines the tool's analytical scope (FMCSA authority, insurance, safety, sanctions, court, federal-award evidence) and differentiates it from sibling carrier tools by emphasizing tender context, disposition outcomes, and fraud-screening purpose.

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 explicitly states when to use the tool: before accepting or dispatching a load. It does not name alternative sibling tools or explicitly state when not to use it, but the use case is clear enough to guide selection among carrier-related siblings.

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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