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Rekvira: EU regulation pinpoints for compliance AI

Verify a citation

verify_citation
Read-onlyIdempotent

Verify a citation someone else produced — does the pinpoint exist in held text, and optionally does the quote appear. Pass the cite as written (e.g. 'Article 6(1) EU AI Act') plus optional quote=. Then read_unit for full text. regulation= disambiguates when the cite omits the act name; returns regulation_mismatch when the cite embeds YYYY/NNNN for a different act.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
citeNoAlias for citation when agents pass cite= instead of citation=
as_ofNoOptional date YYYY-MM-DD: answer with the wording in force on that date (default today). Amended provisions say which act gave them their wording
quoteNoOptional sentence to check against held text
citationNoCitation as written, e.g. Article 6(1) EU AI Act
regulationNoRegulation id when the cite string alone is ambiguous

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / as_of
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Optional date YYYY-MM-DD: answer with the wording in force on that date (default today). Amended provisions say which act gave them their wording",
      +  "title": "As Of"
      +}
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, and idempotentHint, so the safety profile is covered. The description adds meaningful behavioral detail beyond that: it mentions the regulation_mismatch return condition when the cite embeds YYYY/NNNN for a different act, and clarifies that the tool checks pinpoint existence and quote presence. This is valuable context not captured in structured fields.

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?

The description is concise but information-dense. It opens with the core purpose, then gives usage instructions, points to a related tool, and notes a specific return condition. It is structured logically and avoids fluff, though it is slightly longer than strictly necessary due to the parenthetical example and multiple clauses.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main use case, optional parameters, disambiguation logic, and a specific error return (regulation_mismatch). However, there is no output schema, and the description does not explain what the tool returns on success (e.g., a boolean, a result object, or a match/mismatch indication). An agent needs to know the output shape to interpret results, which is a notable gap. The as_of parameter is also only documented in the schema, not in the description, though that is less critical.

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 the baseline is 3. The description goes beyond the schema by explaining how to pass the cite as written with an example, and clarifies that regulation= disambiguates when the act name is omitted, tying two parameters together. It also mentions the optional nature of quote. This adds practical meaning beyond the individual field descriptions.

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 verifies a citation someone else produced, checking whether the pinpoint exists in held text and optionally whether the quote appears. It gives a concrete example input and explicitly points to read_unit for full text, distinguishing it from related tools like search_regulations.

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 provides usage guidance by instructing to pass the cite as written, optionally include quote, and then use read_unit for full text. It also explains that regulation= disambiguates when the cite omits the act name. However, it does not explicitly contrast with alternative tools like search_regulations or state when not to use this tool, so it stops short of a full when/ when-not matrix.

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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