GlyphGuard

Scan text for hidden or deceptive Unicode

scan_text

Read-onlyIdempotent

Find invisible characters, bidi controls (Trojan Source), hidden Unicode tag payloads (decoded), variation-selector runs, control characters, unusual spaces, mixed-script words and lookalike letters. ZWJ/ZWNJ/VS16 in legitimate context (emoji sequences, Persian/Arabic joining, Indic virama) are reported as info joiner_in_context and do not raise risk; elsewhere they stay medium. Lone surrogates are flagged. Returns a risk level (none/low/medium/high), counts, and findings with UTF-16 offsets and code points. Read-only. Same engine as GET /api/scan.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "scan_text"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes	Text to inspect (up to 2000 UTF-16 code units).

Output Schema

Name	Required	Description	Default
`risk`	Yes
`notes`	No
`total`	Yes
`counts`	Yes
`length`	No
`version`	Yes
`findings`	Yes
`truncated`	No
`codePoints`	No
`tagPayload`	No
`normalizedNfkcDiffers`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 22, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare read-only/idempotent/non-destructive, so the bar is lower, and the description still adds real value: it explains the risk-tiering logic (ZWJ/ZWNJ/VS16 in legitimate emoji, Persian/Arabic joining, or Indic virama contexts downgrade to info joiner_in_context, otherwise medium) and notes lone surrogates are flagged. That conditional-severity policy is behavioral nuance not present in any structured field.

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 detection list is front-loaded and every clause names a distinct finding category, so density is earned. The trailing 'Read-only. Same engine as GET /api/scan.' is slightly redundant against the annotations but is short and provides consistency context.

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?

With an output schema present, the description needn't restate return shape, yet it still summarizes risk level, counts, findings, UTF-16 offsets and code points. Detection categories, edge-case exceptions, and severity policy are all covered; the only gap is how it fits into a workflow with clean_text.

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?

Only one parameter and schema coverage is 100% including the 2000 UTF-16 unit limit, so the schema does all the work. The description never mentions the input bound or what counts as valid text, so it adds nothing beyond structured data — baseline 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?

Opens with a specific verb ('Find') and enumerates the concrete resource classes it detects: invisible characters, bidi controls, tag payloads, variation-selector runs, mixed-script words, lookalikes. That enumeration makes it unmistakably a detection-only scanner, distinct from clean_text (which would mutate) and compare_names (which compares).

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

Usage Guidelines3/5

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

Usage is implied by the detection framing and 'Read-only', but there is no explicit when-to-use statement and no routing to siblings — nothing says whether to run this before clean_text or how it relates to compare_names. The 'Same engine as GET /api/scan' line is endpoint parity, not usage guidance.

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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