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EUR-Lex

by io.github.pipeworx-io

Compliance Index

compliance_index
Read-onlyIdempotent

Resolve a common EU regulation name to its CELEX id. Returns the curated map of the EU digital/compliance corpus (GDPR, NIS2, DORA, AI Act, DSA, DMA, eIDAS, Cyber Resilience Act, Data Act, …) with CELEX ids, types, dates and one-line summaries. Use this first to turn a name like "GDPR" into the CELEX id the other tools need.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional filter — name/alias/keyword (e.g. "AI Act", "data"). Omit to list the whole corpus.

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds return map details but no additional behavioral traits like error handling or authorization. With strong annotations, the description's extra context is moderate.

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 concise sentences: first states the core action, second provides usage guidance and return summary. No unnecessary words, front-loaded purpose.

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 simple lookup tool with one optional parameter and no output schema, the description fully informs the agent: what it returns (map of EU corpus with CELEX ids, types, dates, summaries), how to use it (with or without query), and its role in the workflow. No missing information given the tool's simplicity.

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?

The schema covers the single optional 'query' parameter with examples. The description adds 'name/alias/keyword' clarification and omission behavior, but this is marginal given 100% schema coverage. Baseline 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 resolves a common EU regulation name to its CELEX id, a specific verb+resource pair. It also describes the returned map with details, distinguishing it from sibling tools like search_legislation or get_article which operate on different granularity.

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?

The description explicitly says 'Use this first to turn a name like 'GDPR' into the CELEX id the other tools need,' providing clear guidance on when to use it as a prerequisite. It also explains the optional filter behavior ('Omit to list the whole corpus').

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

A3.7/5.0
Disambiguation1/5

Multiple tools appear to do nearly the same thing: ask_pipeworx, ask_ipeworx_beta (explicitly identical at the moment), ask_pipeworx_grounded, deep_research, and validate_claim all route questionanswering in a very similar way. Even with long descriptions, the sheer number of overlapping query/research/analysis tools (ai_visibility_check vs scan_comperitor_ai_presence, all polymarket_*) would make an agent uncertain which to call.

Naming Consistency2/5

The set uses snake_case everywhere but that is the only consistent part. There is a mess of verb_noun patterns, noun_verb patterns (cjeu_search vs search_legislation, cj_judgment vs get_document), bare noun phrases (entity_profile, compliance_index, pipeworx_feedback, polymarket_edges), and verb phrases (ask_ipeworx, generate_elms_txt, resolve_entry). A user cannot predict whether the noun comes first, so naming is readable but not predictable.

Tool Count2/5

39 tools is far over the 25+ threshold for a coherent set, and a large number of them (predictor markets ten, AI visibility, memory, subscriptions, pipework meta-tools) are outside the EUR-Lex legal research domain. The total count suggests a bundled everything-server rather than a focused legal-research MCP. It is not extreme enough for a 1 because 39 is still within a region where a broader meta-pipework suite could plausibly exist — but it's still too many.

Completeness4/5

For the EUR-Lex domain, the legal tools are nearly complete: search_legislation + compliance_index locate acts, get_metadata/list_articles/get_article/get_document read them, and cjeu_search/cjeu_judgment cover case law. Missing links that would make it fully seamless are amendment tracking, cross-references and direct CELEX/EURL-Lex citation search integration, but all basic 'find and read an act or judgment' workflows are supported.

Resources