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anonymize_file

Replace personally identifiable information in Czech legal documents with pseudonyms to protect privacy during LLM processing. Supports PDF, DOCX, MD, and TXT files with configurable detection depth.

Instructions

Anonymizuje soubor (PDF, DOCX, MD, TXT) — nahradí PII pseudonymy.

Args: file_path: Absolutní cesta k souboru ke zpracování. depth: Hloubka detekce ("thorough" nebo "quick"). output_path: Výstupní cesta (volitelné). Výchozí: vedle originálu s příponou _anonymized.txt.

Returns: anonymized_path: Cesta k výstupnímu souboru s anonymizovaným textem. mapping_id: UUID pro pozdější deanonymizaci. UCHOVEJTE! entity_count: Počet nalezených entit. entities_summary: Počty entit dle typu. source_format: Formát vstupního souboru (pdf/docx/txt/md).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
depthNothorough
output_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it replaces PII with pseudonyms, generates a mapping ID for later deanonymization (with strong warning to preserve it), and returns detailed statistics. It doesn't mention permissions, rate limits, or error conditions, but covers the core transformation behavior adequately.

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?

Perfectly structured with a clear opening sentence stating purpose, followed by organized sections for Args and Returns. Every sentence earns its place, providing essential information without redundancy. The Czech language doesn't affect conciseness scoring.

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?

Given the tool's complexity (file processing with PII detection), no annotations, and the presence of an output schema, the description is remarkably complete. It explains the transformation process, parameters, return values (though output schema exists), and critical behavioral details like the mapping ID preservation requirement.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining all three parameters: file_path (absolute path to process), depth (detection depth with enum values), and output_path (optional with default behavior). It provides crucial semantic information not in the schema, including default values and file naming conventions.

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 specific action ('anonymizuje' - anonymizes) and resource ('soubor' - file) with supported formats listed (PDF, DOCX, MD, TXT). It distinguishes from sibling 'anonymize_text' by specifying file processing rather than text input, and from 'deanonymize' by being the forward operation.

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?

The description provides clear context for when to use this tool (anonymizing files with PII) and implicitly distinguishes from 'anonymize_text' by specifying file input. However, it doesn't explicitly state when NOT to use it or mention all alternatives like 'deanonymize' for reverse operations.

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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