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detect_auth

Scan network traffic to identify authentication schemes—bearer tokens, session cookies, API keys, or signed requests—and get sample flow IDs for inspection.

Instructions

Scan all traffic and report which authentication schemes the site uses.

Run this when picking up an unfamiliar target: it answers "what exactly do I have to forge in order to call this API without a browser?" — a bearer token, a session cookie, a custom API-key header, or a signed request. Each finding includes sample flow ids you can pass straight to inspect_flow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden of explaining behavior. It discloses that the tool scans all traffic, reports auth schemes, and that findings include sample flow ids. This goes beyond the empty input schema and gives useful implementation detail about the result format.

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 compact and front-loaded with the core purpose, followed by the when-to-use guidance and a practical pointer to a sibling tool. Every sentence adds value and there is no redundant restating of the tool name.

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?

For a zero-parameter tool with an output schema, the description is complete: it explains when to run it, what it reports, and how to use the results downstream. The reference to inspect_flow contextualizes the output within the sibling toolset.

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

Parameters4/5

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

The input schema has zero parameters, so the baseline is 4. The description adds context about what the tool does with no arguments and what kind of output to expect, which is sufficient for an agent to invoke it correctly.

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 verb ('scan and report') and a clear resource ('which authentication schemes the site uses'). It is immediately distinguishable from sibling tools like inspect_flow or list_flows because it addresses the high-level question of what credentials/mechanisms are needed.

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?

It gives an explicit trigger: 'Run this when picking up an unfamiliar target.' It also names a specific follow-up tool (inspect_flow) and explains how the output feeds into it. It does not explicitly list when not to use it, but the intended context is clear.

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