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xray

Read-onlyIdempotent

Detect hidden AI-targeted payloads in markdown, HTML, code, and text before an agent consumes them. Expose concealed instructions, invisible Unicode, encoded payloads, and CSS-hidden content.

Instructions

X-ray content for hidden AI-targeted payloads. Detects concealed instructions in markdown, HTML, code, and text before an agent consumes it, including hidden comments, invisible unicode, CSS-hidden text, encoded payloads, code comments, and structural hiding tricks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoFormat hint. Default auto-detects from content.auto
sourceNoOptional source context (for example: README.md, skill-file.md, API response).
contentYesThe raw content to x-ray. Paste the full text of any file, document, or response.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, and the description does not contradict them. It adds useful behavioral context by detailing the classes of hidden content it detects, such as invisible unicode, CSS-hidden text, and encoded payloads.

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 a single front-loaded sentence that states the core purpose immediately, followed by a compact enumeration of detection categories. There is no filler or repetition of schema details.

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?

Schema, annotations, and purpose are sufficient for selecting and invoking the tool. However, since there is no output schema and the description doesn't state what a call returns (e.g., a list of findings, a report, or a risk score), an agent has some ambiguity about how to consume the result.

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 covers 100% of parameters with descriptions for content, format, and source. The tool description adds no per-parameter meaning beyond what the schema already provides, so the baseline of 3 applies.

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 states a specific action (x-ray/scan) and a specific target (hidden AI-targeted payloads in markdown, HTML, code, and text). It lists concrete detection categories, which clearly distinguishes it from siblings like agentscore and sweep.

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?

The description explicitly frames when to use the tool: before an agent consumes untrusted content. It doesn't name alternatives or exclusions, but the use case is clear enough that an agent can decide when this tool is appropriate.

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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