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redact_data_file

Read a sensitive data file and return a redacted preview with masked values. Sensitive columns are pseudonymized consistently to preserve record linkage without exposing raw identifiers.

Instructions

Read a sensitive data file and return a REDACTED preview (masked values).

The redaction half of /safe-analysis: where check_data_safety only *detects*
sensitive data and the read-hook *asks*, this returns a masked version so an
approved read shares no raw identifiers. Sensitive columns (patient/case IDs,
names, GPS, etc.) are pseudonymised consistently — the same value always maps
to the same placeholder, so record linkage survives while identity does not.
PII patterns (emails, phones, IDs) are scrubbed from all remaining cells.

Local I/O only — nothing leaves the machine except the masked preview you see.

Args:
    path:     Absolute local path to a CSV/TSV/text data file.
    max_rows: Rows to include in the masked preview (default 20).

Returns JSON: redacted preview rows, the columns masked, and a per-type count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
max_rowsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, so description carries full burden. It discloses pseudonymisation consistency, PII scrubbing, that the output is a masked preview (not modifying the file), and the local-only nature. No contradictions with annotations.

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?

Description is concise (~150 words) and well-structured: one-line summary, context with alternatives, details on pseudonymisation and local I/O, then args section, and return format. Front-loaded with key information, no redundant sentences.

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 output schema exists and no annotations, description adequately explains return JSON contents (preview rows, masked columns, per-type counts). It covers file types, constraints, and usage context relative to sibling tools. Completely sufficient for agent to select and invoke correctly.

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?

Schema has 0% description coverage, but the description compensates fully by detailing both parameters: 'path' as absolute local path and 'max_rows' as rows in masked preview with default 20. This adds meaning beyond the schema's type and default fields.

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?

Description clearly states it reads a sensitive data file and returns a redacted preview, distinguishing itself from check_data_safety and read-hook via explicit comparison. It specifies verb 'read' and resource 'sensitive data file' with a unique output type (masked preview).

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?

Explicitly positions itself as the redaction half of /safe-analysis, contrasting with detection (check_data_safety) and asking (read-hook). Provides when-to-use guidance, local I/O constraint, and acceptable file formats (CSV/TSV/text).

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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