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redact_text

Mask likely sensitive patterns such as card numbers, IBANs, emails, phone numbers, and API keys in outbound or MCP-bound text before it leaves the server.

Instructions

Redact likely sensitive patterns from outbound/MCP-bound text (IBAN, cards, emails, tokens, etc.). Heuristic output DLP only — not for scrubbing local prompts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoRule ids to skip, e.g. email, phone_eu, card
textYesText to redact

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses an important behavioral trait: the redaction is 'heuristic output DLP only', which sets expectations about reliability and false positives/negatives. However, it does not state whether redaction is reversible, what the output looks like (replacement tokens vs removal), or whether the operation is side-effect free.

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 short, dense sentences with no waste. The primary purpose and critical limitation are both front-loaded and easy to parse.

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?

Given no annotations and no output schema, the description should ideally cover what the redacted output looks like and any limits of the heuristic. It covers the use case well but leaves return-format and reliability details unstated. Adequate but with clear gaps.

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 both parameters are already documented in the schema, including examples for skip rule ids. The description adds no parameter-level detail beyond what the schema provides. Baseline 3 is appropriate.

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?

States a specific verb (redact) and resource (sensitive patterns) with an explicit scope: 'outbound/MCP-bound text'. The parenthetical examples clarify what counts as sensitive. It doesn't explicitly differentiate from siblings, but siblings (list_local_models, ask_local) are unrelated, so no differentiation is needed.

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?

Gives clear context of when to use it (outbound/MCP-bound text) and explicitly says when not to use it ('not for scrubbing local prompts'). No named alternatives, but the use-case boundary is well defined.

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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