Skip to main content
Glama
identity-aiops

identity-aiops

mfa_coverage_analysis

Read-only

Analyze MFA coverage: calculate overall percentage, list users without second-factor authentication, and identify factor types. Samples users via bounded credential pulls.

Instructions

[READ] Second-factor coverage: overall %, the users without MFA, and the factor types counted. Pulls one credential list per user (bounded).

Args: max_users: Users to sample (default 200 — one API call each). target: IdP target name from config; omit for the default.

Returns "inputsTruncated": true when the realm is larger than max_users — coveragePct then describes the sample, not the realm.

Input Schema

NameRequiredDescriptionDefault
targetNo
max_usersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, it discloses the cost model ('one credential list per user', 'one API call each'), the bound (max_users default 200), and the truncation contract ('Returns "inputsTruncated": true when the realm is larger than max_users — coveragePct then describes the sample, not the realm'). That last point is exactly the kind of correctness-critical caveat annotations cannot carry.

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?

Front-loaded with the [READ] marker and one-line purpose, then a tight Args block and a return caveat. Every sentence earns its place; the formatting is slightly mechanical but not padded.

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 no output schema, the description supplies the key return semantics (coveragePct, inputsTruncated). It stops short of naming the full returned structure (e.g., the without-MFA user list and factor-type breakdown fields), but the essentials for correct interpretation are present.

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?

Schema description coverage is 0%, so the description carries the full burden, and it does: max_users is defined as the sample size with default and per-call cost, target as the config IdP name with omit-for-default behavior. It falls short only on enumerating valid target values.

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?

States a specific resource and scope: 'Second-factor coverage: overall %, the users without MFA, and the factor types counted.' No sibling covers MFA coverage, so an agent can route here unambiguously from the tool name plus this line.

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 (an audit/reporting read) but there is no explicit when-to-use, when-not-to-use, or named alternative among the audit siblings like identity_overview or stale_access_audit. The truncation note hints at when the result is partial, but the agent must infer the selection context.

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