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LiveDataLink

by io.github.blackboxfoundry

lane_location_risk_pack

Read-onlyIdempotent

Compare origin and destination risk for a logistics lane. Runs site-bound hazard/environmental profiles for both addresses and optionally adds FEMA disaster history for each area. Returns source coverage, point-in-time risk evidence, and an operational review checklist. This is informational public-record synthesis, not an insurance rating or route guarantee.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoReport format. Defaults to markdown.
origin_areaNoOptional origin county/place for FEMA history.
origin_stateNoOptional origin 2-letter state, required with origin_area.
origin_addressYesFull US origin street address.
destination_areaNoOptional destination county/place for FEMA history.
destination_stateNoOptional destination 2-letter state, required with destination_area.
destination_addressYesFull US destination street address.

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive. The description adds valuable context by stating it's informational public-record synthesis and not a rating or guarantee, and notes point-in-time evidence. This goes beyond annotations without contradicting them.

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?

Two sentences with no fluff. The first sentence states the core purpose, the second lists key outputs and adds a disclaimer. Front-loaded and efficient.

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 7-parameter tool with 100% schema coverage and no output schema, the description adequately explains what it returns (source coverage, point-in-time risk evidence, operational checklist) and its informational nature. Enough for an agent to decide and invoke.

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 carries full parameter meaning. The description reiterates optional FEMA history but does not add new meaning beyond what the schema already provides. Baseline of 3 is appropriate.

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 clearly states the tool compares origin and destination risk for a logistics lane, explicitly mentioning it runs hazard/environmental profiles and optionally FEMA disaster history. This distinguishes it from single-location siblings like environmental_site_risk and location_risk_report.

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

Usage Guidelines3/5

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

The description implies use for comparative lane risk assessment but does not explicitly mention when to use it over alternatives. It provides a negative disclaimer (not insurance rating or route guarantee) but lacks direct guidance on alternative tools or conditions for use.

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