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fairquery

fairquery-agent-trust-mcp

Official

List covered sanctions lists (free)

sanctions_list_sources
Read-onlyIdempotent

Fetch official sanctions list sources, scoring scale, and legal disclaimer to choose lists, cite authorities, and explain coverage before paid screening.

Instructions

WHAT: Static list of the official sanctions lists sanctions_screen_names checks (id, name, authority, download URL), the score scale and the legal disclaimer. WHEN: To choose the lists parameter, cite sources in a report, or explain coverage before paying. WHEN NOT: To screen a name (sanctions_screen_names, paid). It does not download lists or report freshness. COST: Free. Static local data; no network, no token. RETURNS: {sources:[{id,name,authority,url}],score_scale,disclaimer,pricing}. EXAMPLE: {} -> {"sources":[{"id":"OFAC_SDN","authority":"US Treasury OFAC",...},...]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pricingYes
sourcesYes
disclaimerYes
score_scaleYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds value beyond them: it is a static local dataset with no network and no token, and it explicitly does not download lists or report freshness — a meaningful limitation an agent must know.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with labeled WHAT/WHEN/WHEN NOT/COST/RETURNS/EXAMPLE blocks and strong front-loading. However, the RETURNS block and the JSON example partially restate the already-provided output schema, so a small amount of content does not earn its place.

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 zero-parameter, read-only listing tool with an output schema available, the description covers purpose, usage routing, cost, and behavioral limits completely. No gap remains that would cause an agent to call it incorrectly.

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?

The tool takes zero parameters, so the baseline is 4. The description's only parameter reference is to a sibling's 'lists' parameter, which adds context but no schema meaning for this tool itself.

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?

States a specific resource (static list of official sanctions lists sanctioned by sanctions_screen_names) and the exact fields returned (id, name, authority, download URL). Explicitly distinguishes itself from the sibling paid screening tool, so an agent can select it without opening either schema.

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?

Provides explicit WHEN (choose the lists parameter, cite sources, explain coverage before paying) and WHEN NOT (screening a name, which is sanctions_screen_names, paid). Names the alternative and the condition selecting it, including cost implications.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.