Skip to main content
Glama
IAZENT

HuntX

Official
by IAZENT

xss_scan

Probe request parameters with XSS payloads to identify unescaped reflections, flagging confirmed and likely vulnerabilities.

Instructions

Probe a request's query/body parameters for reflected XSS.

Injects a unique marker wrapped in an HTML-breaking payload per parameter and statically analyzes the response: verbatim unescaped reflection is "confirmed", reflected-but-transformed is "likely" (needs human/browser verification), properly encoded or not-reflected-at-all produces no finding at all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL to test.
bodyNoOptional JSON request body.
paramNoTest only this query param / body field by name. If omitted, tests every discovered injectable param.
methodYesHTTP method (GET, POST, etc.).
headersNoOptional request headers.
target_idYesIdentifier for the target.
scope_excludeNoScope denylist patterns.
scope_includeNoScope allowlist patterns.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses the methodology: a unique marker wrapped in an HTML-breaking payload is injected per parameter and the response is statically analyzed. It also explains the triage output semantics—confirmed, likely, or no finding—which is critical for interpreting results and avoiding false confidence.

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?

Two compact paragraphs with a front-loaded main action and a tight, information-dense follow-up. The classification detail in the second paragraph is necessary for safe interpretation, and no sentence is wasted.

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?

The description covers what is tested, how it is tested, and how findings are classified, which is enough for an agent to select and invoke the tool. Since an output schema exists, the description need not spell out return fields; the scanner-specific behavioral nuance is fully addressed.

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 description coverage is 100%, so the schema already explains url, body, method, headers, scope filters, and the param override. The description adds general context about query/body parameters and per-parameter testing but does not add meaning on top of the schema for individual parameters.

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 opens with a specific verb-resource pair: 'Probe a request's query/body parameters for reflected XSS.' This clearly distinguishes xss_scan from sibling scanners like sqli_scan, ssrf_scan, and ssti_scan by naming the exact vulnerability class and injection surface.

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?

The intended use (reflected XSS detection) is implied by the purpose statement, but the description gives no explicit 'when to use' guidance and names no alternatives or exclusion criteria. An agent must infer suitability from the tool name and sibling set rather than from direct guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/IAZENT/HuntX'

If you have feedback or need assistance with the MCP directory API, please join our Discord server