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Lucav21

heu-legal-mcp

by Lucav21

extract_pdf_document_parties

Extract party information from uploaded PDFs by merging signer metadata with extracted text fields like tax code, VAT, and address, designed for Italian contracts.

Instructions

Estrae i dati anagrafici delle parti da un PDF caricato. Combina i metadati dei firmatari registrati con dati estratti dal testo: codice fiscale, P.IVA, codice univoco SDI, email/PEC, luogo e data di nascita, indirizzi, CAP. Pattern ottimizzati per contratti italiani.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idYesID del PDF caricato
pagesNoRange pagine: '1-3', '5', '1,3,5-7'. Default: tutte (max 100).
include_textNoSe true include nel risultato anche il testo grezzo. Default: false.
Behavior3/5

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It mentions combining metadata from registered signers with text extraction, which suggests read-only analysis, but does not explicitly state whether the tool modifies state, requires permissions, or has rate limits. The absence of destructive/read-only hints is a gap.

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 a single sentence but packs substantial information (data fields, source, context). It is efficient and well-structured, though the sentence is somewhat long. No extraneous content.

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

Completeness4/5

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

Given the tool's moderate complexity, no output schema, and no annotations, the description provides enough context by enumerating extracted data fields and noting optimization for Italian contracts. It covers the essential behavioral aspects, though it could benefit from mentioning whether results include confidence scores or are only from text.

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 the baseline is 3. The description does not add parameter-specific details beyond the schema; it only summarizes overall output. Since schema already documents each parameter, the description adds limited extra semantic value.

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 extracts anagraphic data of parties from a PDF, listing specific data fields (codice fiscale, P.IVA, etc.) and noting optimization for Italian contracts. This is a specific verb+resource and distinguishes it from siblings like 'extract_heu_document_parties' by targeting PDF documents.

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?

The description explains what the tool does but does not provide any guidance on when to use it versus alternatives (e.g., 'extract_heu_document_parties') or when not to use it. Usage context is implied from the purpose, but no explicit exclusions or prerequisites are given.

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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