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EUR-Lex

by io.github.pipeworx-io

Cjeu Judgment

cjeu_judgment
Read-onlyIdempotent

Get the FULL TEXT of an EU court judgment from its case number — "C-97/23", "T-144/25" — or its CELEX id. Resolves the case number people actually cite into the document. Use after cjeu_search, or whenever a case number appears in a filing or article.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offsetNoCharacter offset, for paging through a long judgment (default 0).
max_charsNoMax characters to return (default 12000, max 40000).
case_numberYesAs cited, e.g. "C-97/23" (Court of Justice) or "T-144/25" (General Court). A CELEX id like "62023CJ0097" also works.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful context about resolving user-facing case numbers into official documents, which is a behavioral trait not captured by annotations. No contradictions.

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, front-loaded with the action and object, includes examples and usage direction. Every phrase earns its place with zero filler or redundancy.

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?

The tool is simple (one required parameter, two optional paging parameters). The description, annotations, and schema together fully explain when and how to use it. The lack of an output schema is mitigated by the clear promise of 'FULL TEXT' and the paging parameters.

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?

Input schema has 100% coverage with clear parameter descriptions, so the schema carries the semantic load. Description slightly reinforces that case_number accepts both case-number and CELEX formats, but this is already stated in the schema, adding no extra value beyond the baseline.

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?

Description starts with a specific verb ('Get') and a clear resource ('FULL TEXT of an EU court judgment'), provides concrete input examples (C-97/23, T-144/25), and distinguishes from the sibling tool cjeu_search by noting it 'resolves the case number people actually cite into the document.'

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?

Explicitly states when to use the tool: 'Use after cjeu_search, or whenever a case number appears in a filing or article.' This provides concrete trigger conditions and implicitly names the alternative (cjeu_search).

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.

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