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pablixnieto2

ETL-D MCP Server

by pablixnieto2

redact_pii_v1_enrich_redact_pii_post

Redact personally identifiable information (PII) from text locally with GDPR/HIPAA compliance. Specify language and entity types for targeted redaction.

Instructions

Enterprise-grade PII Anonymizer. Runs 100% locally in RAM. No external LLMs are used. Fully compliant with GDPR/HIPAA for Zero Data Retention.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text containing PII to be redacted.
languageNoLanguage of the text ('en' or 'es')en
entities_to_redactNoOptional list of entity types to redact (e.g., ['PERSON', 'EMAIL_ADDRESS', 'PHONE_NUMBER']). If not provided, all supported entities will be redacted.
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does add useful context: it runs locally in RAM, uses no external LLMs, and claims GDPR/HIPAA compliance. However, it omits what the tool returns (e.g., redacted text), error behavior, or any side effects. It adds some value but not comprehensive transparency.

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 two sentences with no filler. It opens with the primary purpose and follows with compliance details. Every sentence earns its place; the structure is front-loaded and efficient.

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

Completeness3/5

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

For a tool with three parameters and no output schema, the description leaves gaps. It doesn't specify what the tool returns (e.g., the redacted text), how it handles unsupported languages, or what 'all supported entities' includes. It's adequate but not fully complete for an agent to call it correctly without further inference.

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?

All three parameters have descriptions in the schema (100% coverage), so the description doesn't need to add parameter-level detail. It doesn't, but the baseline of 3 is appropriate because the schema handles the semantic explanation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool is a 'PII Anonymizer', which conveys a specific verb and resource. It doesn't explicitly mention 'redact' but 'anonymize' is synonymous in this context. The purpose is distinct from sibling tools like enrich_name or dedupe_items, but the description doesn't call out those differences, so it doesn't earn a 5.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. The description doesn't mention any conditions, prerequisites, or alternatives, leaving the agent to infer usage solely from the tool name and schema.

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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