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Auth Surface

auth_surface
Read-only

Detect authentication endpoints on given hosts and rank them by account-worthiness, guiding manual registration for later authorization testing.

Instructions

Detect authentication functionality and rank hosts by account-worthiness.

target takes one host or a comma-separated list — normally the live URLs http_probe found, which is how scripts/hunt.sh chains it. Targets are scope-checked before this body runs, so the list cannot be widened here.

Every request is a GET against a conventional path. Nothing is submitted, no account is created, and no credential is sent. The output is a recommendation to a human: register on these hosts, by hand, if the program's rules permit it — then bring the sessions back with session_register and authz_compare can finally test authorization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes
timeoutNo
max_hostsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv2.1.0

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description adds specific behavioral details: 'Every request is a GET against a conventional path. Nothing is submitted, no account is created, and no credential is sent.' This fully clarifies the tool's safe, non-intrusive nature.

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 description is slightly verbose with multiple paragraphs, but each sentence serves a purpose—purpose, usage context, safety, and output—so it remains well-structured and not overly long.

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?

The description covers what the tool does, how it's used in a pipeline, its safety, and its output ('a recommendation to a human'). It also mentions next steps (session_register, authz_compare), providing sufficient context for an agent to decide when to invoke it.

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 the 'target' parameter is explained ('takes one host or a comma-separated list'). The other parameters ('timeout' and 'max_hosts') are not described, and schema description coverage is 0%, so the description must compensate but only does so partially.

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 clearly states the tool's purpose with a specific verb ('Detect' and 'rank') and resource ('authentication functionality' and 'hosts by account-worthiness'). It distinguishes itself from sibling tools like authz_compare and account_register by focusing on detection and ranking for manual registration.

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 provides context on when to use it: 'normally the live URLs `http_probe` found' and that it's part of a script chain. It also explains the intended workflow (register manually, then use session_register and authz_compare). While it doesn't explicitly compare to alternatives, the usage context is clear.

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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