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redact_trace

Removes secrets and personal data from trace or log excerpts, returning cleaned text safe to paste into tickets.

Instructions

Remove secrets and personal data from a trace or log excerpt, returning the cleaned text.

Removes API keys and tokens (JWT, Bearer, AWS, GitHub, Slack, Stripe, Google, sk-...), password=/token= style values, credentials in URLs, emails, IPv4 and full IPv6 addresses, and user names in home directories (C:\Users\name, /home/name, /Users/name). Safe to run before pasting a trace into a ticket. Every other tool also redacts its output by default.

Args: text: Text to clean (max 5,000,000 characters).

Input Schema

NameRequiredDescriptionDefault
textYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the operation is purely a read-and-return transform (nothing mutated or destroyed), enumerates exactly which patterns are stripped, and gives a 5,000,000-character input ceiling. It omits any statement about failure modes or what happens to text that partially matches, which keeps it off a 5.

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 core action and scope are front-loaded in sentence one, the redaction inventory is packed into a single compact parenthetical, and the practical guidance plus the args note close it out. No sentence is filler.

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?

The tool is a simple one-parameter transform with an output schema, so return values need no explanation and the description correctly says only that cleaned text comes back. Between the annotated behavior, the redaction inventory, and the size limit, an agent has everything needed to call it correctly.

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

Parameters4/5

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

Schema coverage is 0% and the single property is a bare string, so the description must compensate — and it does, supplying both the meaning ("Text to clean") and a hard limit ("max 5,000,000 characters") that appears nowhere in the schema. That is meaningful semantics added beyond the input schema, though the limit could have stated the consequence of exceeding it.

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?

States a specific verb and resource ("Remove secrets and personal data from a trace or log excerpt") and describes the return value ("returning the cleaned text"). The enumerated redaction categories (API keys, JWTs, credentials in URLs, emails, IPs, home-directory usernames) make it unmistakable versus siblings like parse_trace or fingerprint, which do structural work rather than sanitization.

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?

"Safe to run before pasting a trace into a ticket" gives a concrete usage context, and "Every other tool also redacts its output by default" usefully tells the agent this is only needed for raw external text, implicitly scoping out redundant calls. It stops short of naming a specific sibling alternative or an explicit when-not-to-use case, so it lands just below the top band.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.