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lambda-labs

by io.usefulapi

List audit events

lambda_list_audit_events
Read-only

List account audit-log events, optionally filtered by time window and resource type, with page_token pagination. Lambda Cloud REST: GET /api/v1/audit-events.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoOnly events at/before this ISO 8601 timestamp.
startNoOnly events at/after this ISO 8601 timestamp.
page_tokenNoPagination token — pass the value returned by a previous page to fetch the next.
resource_typeNoRestrict to events on this resource type (e.g. 'instance', 'filesystem').

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, and the description adds the GET endpoint and pagination behavior, which is useful context. However, it doesn't disclose any other behavioral traits like rate limits or return format. The added info partially overlaps with the schema, so it doesn't go far beyond the annotation baseline.

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 a single, front-loaded sentence that states the primary action, optional filters, pagination, and REST endpoint. Every word earns its place, with no redundancy or filler.

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 simple read-only list tool with no output schema, the description is sufficiently complete. It covers the purpose, filtering, pagination, and endpoint. It doesn't explain return-values format, but that's not necessary given the tool's straightforward nature and the absence of an output schema.

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?

The schema provides 100% description coverage for all 4 parameters, so the baseline is 3. The description mentions 'time window' and 'resource type' as a summary but doesn't add any meaning beyond what the parameter descriptions already state. No extra syntax or formatting details are provided.

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 ('List') and resource ('account audit-log events'), clearly distinguishing it from sibling list tools like list_instances or list_images. It also mentions optional filters and pagination, making the tool's purpose unambiguous.

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?

The description provides clear context on when to use the tool (to list audit events) and describes optional filtering and pagination. It doesn't explicitly name alternatives or exclusions, but no sibling tool covers audit logs, so a 4 is appropriate.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct resource and action (e.g., list_instances vs. launch_instance vs. terminate_instances). There is no overlap or ambiguity between tools; even similar resources like firewall_rules and firewall_rulesets are clearly differentiated by name and description.

Naming Consistency5/5

All tool names follow the verb_noun pattern with the lambda_ prefix, using lowercase and underscores consistently. The verb clearly indicates the operation (list, get, create, delete, launch, update, restart, terminate), and the noun indicates the resource. Minor pluralization differences (e.g., list_instances vs. get_instance) are conventional and do not break consistency.

Tool Count5/5

15 tools is well-scoped for a GPU cloud management server, covering instances, filesystems, firewall rules, images, instance types, and audit events. Each tool serves a distinct purpose and no unnecessary duplication exists.

Completeness4/5

The instance lifecycle is well covered with launch, get, list, update, restart, and terminate. Filesystem and firewall read operations are present, but firewall rule/ruleset management (create/update/delete) is missing, which is a minor gap that may require working around via the dashboard.

Resources