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AIops-tools

identity-aiops

login_events

Retrieves recent authentication events with filters for event type and user. Enables investigation of login failures and audit of sign-in activity across Keycloak and Authentik.

Instructions

[READ] Recent authentication events, normalized (time/type/user/ip/client/error).

Args: event_type: Platform vocabulary — Keycloak LOGIN / LOGIN_ERROR, authentik login / login_failed (case-insensitive). user: Optional username / user-id filter. max_results: Page bound (default 200, max 500). target: IdP target name from config; omit for the default.

Returns {"events": [...], "returned": N, "limit": L, "truncated": bool}. truncated is measured (one extra event is fetched), not guessed — when it is true, more events exist; re-run with a higher max_results rather than treating the partial feed as the whole picture. Optional fields an event did not carry are null, never "".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userNo
targetNo
event_typeNo
max_resultsNo
Behavior5/5

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

The description explicitly discloses the truncation behavior ('truncated is measured (one extra event is fetched), not guessed') and the null-handling convention ('Optional fields ... are null, never \"\"'). These are valuable behavioral details beyond the bare read operation, especially since no annotations are provided.

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 tightly structured with 'Args' and 'Returns' sections, ~140 words, with every sentence contributing info (vocabulary, pagination semantics, null convention). No fluff or repetition.

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?

With no output schema, the description fully specifies the return shape ({\"events\": [...]}), the meaning of 'truncated', and how to handle partial feeds. It also covers all four parameters with actionable details, making the tool complete for an agent to select and invoke correctly.

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

Parameters5/5

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

Schema description coverage is 0%, but the 'Args' section adds substantial meaning: it defines the platform vocabulary for event_type (Keycloak LOGIN / LOGIN_ERROR, authentik login / login_failed), explains user as optional username/ID filter, gives max_results default (200) and max (500), and clarifies target as an IdP target name from config. This far exceeds the bare schema types.

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 '[READ] Recent authentication events' with a specific verb (read) and resource (authentication events), and lists normalized fields (time/type/user/ip/client/error). This clearly distinguishes it from sibling tools like admin_events (admin actions) and login_failure_rca (failure analysis).

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 description implies use for reading recent authentication events but does not explicitly mention when to use it instead of related tools (e.g., admin_events, login_failure_rca). No alternatives or exclusions are named, so guidance remains implicit rather than explicit.

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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