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Rekvira: EU regulation pinpoints for compliance AI

Search all regulations

search_regulations
Read-onlyIdempotent

Sign-in required: call connect(email) and connect_verify first (free, one email) unless this connection is already signed in. Search all loaded regulation modules in one call, ranked by relevance across them. Use when the question names more than one act or you do not know which act holds the answer. limit, detail (compact|full) and max_chars bound the response; per_regulation_min gives each act a share of the page. Each hit carries its regulation id — then read_unit per regulation.

Input Schema

NameRequiredDescriptionDefault
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
kindsNoOptional filter: recital, article, paragraph, annex, section
limitNoMost rows to return (default 10 on searches, max 50)
queryNoSearch terms in English (required)
detailNocompact (default: ~400-char excerpt around the match) | full (whole unit text)
max_charsNoCap on the response size in characters (default 8000)
regulationsNoOptional subset of regulation ids; default = all loaded corpus
per_regulation_minNoOptional: at least this many rows from each act with matches

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. Changed4 schema fields changed
    • addedInput schema / properties / detail
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "compact (default: ~400-char excerpt around the match) | full (whole unit text)",
      +  "title": "Detail"
      +}
    • addedInput schema / properties / limit
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "integer"
      +    },
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Most rows to return (default 10 on searches, max 50)",
      +  "title": "Limit"
      +}
    • addedInput schema / properties / max_chars
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "integer"
      +    },
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Cap on the response size in characters (default 8000)",
      +  "title": "Max Chars"
      +}
    • addedInput schema / properties / per_regulation_min
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "integer"
      +    },
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Optional: at least this many rows from each act with matches",
      +  "title": "Per Regulation Min"
      +}
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds genuinely useful non-annotation context: an auth prerequisite with the exact connect/connect_verify sequence, cross-act relevance ranking, and response-size bounding.

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?

Five dense sentences, front-loaded with the blocking auth prerequisite before purpose, usage, response controls, and the chaining hint. No filler and nothing repeated from the name or title.

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?

With eight optional parameters, no output schema, and a chained read workflow, the description supplies what is otherwise missing: sign-in gating, cross-act behavior, response-size controls, and the fact that each hit yields a regulation id for read_unit.

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 all eight parameters are already documented. The description restates the response-bounding role of limit/detail/max_chars and per_regulation_min's per-act share, which frames their interplay but adds little detail beyond the schema text.

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 verb and resource ('Search all loaded regulation modules in one call') plus the scope that distinguishes it: cross-corpus, relevance-ranked. An agent can tell it apart from the singular search_regulation sibling from the description alone.

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?

Gives an explicit selection condition ('when the question names more than one act or you do not know which act holds the answer') and a follow-up step ('then read_unit per regulation'). It never names the single-act alternative, so the routing is clear but not fully spelled out.

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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