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scan_content

Scan text content to identify AVE security vulnerabilities in agentic AI components. Get findings with severity scores, OWASP categories, and remediation guidance.

Instructions

Scan raw text content for AVE security vulnerabilities.

Use this to check skill file content, system prompts, MCP tool descriptions, or any agentic AI component before using it.

Returns findings with AVE IDs, AIVSS severity scores, OWASP MCP categories, and links to full remediation guidance. Also detects toxic flows where two findings combine into a complete attack chain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe text content to scan (skill file, system prompt, etc.)
labelNoOptional label for the content in the outputsubmitted-content
no_ignoreNoIf True, bypass all suppressions and show every finding

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses that it returns findings with AVE IDs, severity scores, OWASP categories, and remediation links, plus detects toxic flows. However, it doesn't mention whether scanning is read-only, idempotent, or any rate limits/auth requirements.

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?

Three sentences efficiently convey purpose, use cases, and output details. No wasted words, and the action verb 'Scan' is front-loaded, making it immediately clear what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Moderate complexity with 3 parameters and output schema. Description covers purpose, usage, return values, and even the additional capability of detecting toxic flows. Since an output schema exists, return value details are not required, but the description provides useful context. Minor gap: no mention of potential state changes or limitations.

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?

Input schema has 100% description coverage with clear descriptions for all three parameters. The description does not add extra information beyond what's in the schema, so baseline score of 3 is appropriate.

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 scans raw text for AVE security vulnerabilities and lists specific use cases like skill files, system prompts, and MCP tool descriptions. It distinguishes itself from sibling tools that focus on listing, searching, or specific scan types.

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?

Explicitly says to use before using any agentic AI component, providing clear context. While it doesn't list when not to use or name specific alternatives, the sibling tools are named and the description implies this is the general content scanner.

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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