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Lex-API

LexAPI MCP

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by Lex-API

lex_semantic_legislation

Search EU legislation at article level using semantic embeddings. Get relevance-scored results including CELEX ID, article reference, and law title.

Instructions

Embedding-based search over EU legislation at article granularity. Returns relevance-scored article hits with parent CELEX, article reference, and law title. Requires a paid LexAPI plan; returns 403 on FREE tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
limitNo
min_scoreNo
filtersNo
Behavior3/5

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

With no annotations, description carries full disclosure burden. It reveals it's embedding-based, returns relevance scores, and requires a paid plan. However, it omits behaviors like how filters work, pagination, rate limits, or side effects, leaving gaps.

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?

The description is three sentences, each carrying essential information: purpose, output details, and prerequisite. No fluff, front-loaded with key verb and resource.

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

Completeness2/5

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

Given 4 parameters, no output schema, and no annotations, the description is too brief. It fails to explain parameter usage (e.g., what 'filters' accepts, meaning of 'min_score') and does not fully specify return format, leaving significant gaps for agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, and the description does not explain any parameter semantics (query, limit, min_score, filters). It only describes output fields, so the agent lacks guidance on how to configure inputs meaningfully.

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 clearly states it performs embedding-based search over EU legislation at article granularity, and lists specific returned fields (parent CELEX, article reference, law title). This distinguishes it from sibling tools like lex_semantic_case_law (case law) and lex_search (likely keyword search).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description mentions the paid plan requirement but does not explicitly guide when to use this tool versus alternatives (e.g., keyword search or case law semantic search). Usage context is implied but not delineated.

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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