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redact_text

Scan text for secret patterns, replace matches with [REDACTED], and return category labels. Use to preview detections before writing records or to build custom masking logic.

Instructions

Redact secret-shaped text without writing a record.

    Applies the public Nogra secret-pattern filter to caller-provided text and returns the redacted text plus
    category labels for every detected secret-shaped match.

    When to use:
    - Preview which secret-pattern labels Nogra would detect in text before writing it to workspace substrate.
    - Build caller-side masking or display logic from the same labels used by write-time annotations.

    When NOT to use:
    - Do not use this as destructive storage; write-tools annotate records and keep original text.
    - Do not use this for provider handoff receipts; provider_handoff already redacts rendered prompts.

    Examples:
    >>> redact_text("token=sk_test_abcdefghij1234567890")
    {"redacted": "token=[REDACTED]", "redactions": ["api-key-shape"]}
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to scan and return with secret-shaped matches replaced by [REDACTED].

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully bears the burden. It discloses that the tool applies a public filter, returns redacted text and category labels, and does not write or store anything. No contradictions.

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 appropriately sized with clear sections (When to use, When NOT to use, Examples). Each sentence serves a purpose, no wasted words, and the structure aids quick comprehension.

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?

For a simple tool with one parameter and an output schema, the description is fully complete. It explains the purpose, usage context, behavioral constraints, and provides a concrete example, leaving no gaps for an AI agent.

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 100% for the single parameter, so baseline is 3. The description adds value by explaining the output behavior, providing context about secret-pattern filtering, and including an example, which goes beyond the schema's parameter description.

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 'Redact secret-shaped text without writing a record,' specifying the verb (redact) and resource (text). It distinguishes itself from sibling write-tools by clarifying it does not write, which differentiates it effectively.

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

Usage Guidelines5/5

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

Explicit 'When to use' and 'When NOT to use' sections provide clear guidance. It states to use for previewing secret-pattern labels before writing and for building masking logic, and warns against using it for destructive storage or provider handoff receipts.

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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