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hawklithm

sensitive-info-mcp

by hawklithm

mask_text

Detect and mask sensitive information in text using strategies like mask, replace, hash, or redact, with optional AI semantic detection.

Instructions

检测并脱敏文本,返回脱敏后的文本

Args: text: 待脱敏文本 mask_strategy: 脱敏策略 mask|replace|hash|keep_format|redact enable_ai: 是否启用 AI 语义检测

Returns: 脱敏后的文本

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
mask_strategyNo
enable_aiNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It mentions detection and desensitization but does not explain side effects, permission requirements, rate limits, or the exact impact of different mask_strategy options.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with the core purpose stated first. The Args section is well-structured, though it uses a code-style format that could be streamlined. No unnecessary information is present.

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?

The tool has three parameters and sibling tools in a similar domain. The description covers basic functionality but lacks details on output structure (despite an output schema existing) and does not fully explain the behavior of each mask strategy. It is adequate but not thorough.

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?

The input schema has 0% description coverage, so the description must compensate. It lists the three parameters with brief explanations (e.g., mask_strategy options as 'mask|replace|hash|keep_format|redact' and enable_ai as 'enable AI semantic detection'), but does not elaborate on the meaning or effect of each strategy, leaving gaps.

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 the tool's action: 'detect and desensitize text, return desensitized text.' It specifies the resource (text) and verb (mask), and distinguishes from sibling tools like mask_file (which works on files) and scan_text (which scans but does not mask).

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?

The description provides no guidance on when to use this tool versus alternatives such as scan_text or mask_file. It does not mention prerequisites, limitations, or recommended scenarios.

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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