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scan_exposure

Fetches a URL once, classifies any bot wall, and scans the served 64 KB page for exposed key-like material, returning pattern classes and SHA-256 fingerprint prefixes without revealing values.

Instructions

Fetch a URL once with an honest wallcheck user agent — one honest GET, no retries — classify the wall, and scan the served page for key-like material: CANDIDATE_EXPOSURE (server-secret classes that should never be public), PUBLIC_BY_DESIGN (frontend keys and app IDs), and VISITOR_TOKEN (short-lived JWTs). Findings carry pattern, class, value length and a SHA-256 fingerprint prefix — never the value itself. The scan covers the probe's bounded body sample (64 KB), so material served past the cap is out of reach of this tool.

Input Schema

NameRequiredDescriptionDefault
urlYes
timeoutNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A3.7/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so thoroughly: exactly one GET, an honest wallcheck user agent, no retries, a bounded 64 KB body sample, and a clear statement that findings expose only pattern, class, value length and a SHA-256 fingerprint prefix — never the value itself. It also warns that material beyond the cap is out of reach, which is exactly the kind of limitation an agent needs.

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 action is front-loaded and every clause adds substantive information about behavior, findings, or limits. It is dense with em dashes and runs long, but there is little that could be removed without losing required 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?

For a two-parameter tool with no annotations or output schema, the description covers network behavior, scanning scope, finding shapes, and the 64 KB limitation well. The remaining gap is the timeout parameter and any error/timeout behavior, which are not addressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for both parameters. It implies the url argument through 'fetch a URL once' but says nothing about the timeout parameter or its default of 15, leaving a meaningful operational parameter undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource chain — fetch a URL once, classify the wall, scan the served page for key-like material — and names the finding classes. It is clear what the tool does, but it never distinguishes itself explicitly from siblings like probe_url or classify, which overlap with the fetch and classification steps.

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 describing the scan and the categories it reports, so an agent can infer this is for exposure hunting on a single URL. However, there is no explicit when-to-use guidance, no when-not, and no mention of when probe_url or classify would be preferable.

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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