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clickup_audit_log_query

Retrieve ClickUp audit log events for a workspace, filtered by event type, acting user, and date range. Provides visibility into user actions for security audits.

Instructions

Query the ClickUp audit log (who did what, when) for a workspace — filter by event type, acting user, and date range. Requires Enterprise plan. Uses v3 cursor pagination. Returns an array of audit event objects (actor, event, target, timestamp).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoInclusive upper bound as a Unix timestamp in milliseconds. Omit for no upper bound.
start_dateNoInclusive lower bound as a Unix timestamp in milliseconds (e.g. 1735689600000 for 2025-01-01). Omit for no lower bound.
team_idNoWorkspace (team) ID. Obtain from clickup_workspace_list (field: id). Omit to use the default workspace from config.
typeYesAudit event type filter. Required. ClickUp's documented categories include 'AUTH', 'HIERARCHY', 'USER', 'CUSTOM_FIELDS', 'AGENT', 'OTHER'. See ClickUp docs for the full enum.
user_idNoRestrict to events performed by this user ID. Obtain from clickup_member_list. Omit for all users.
Behavior4/5

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

Despite no annotations, the description explains key behaviors: requires Enterprise plan, uses cursor pagination, returns array of audit event objects with specific fields. This adds value beyond the schema by disclosing pagination and return 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?

Three concise sentences: purpose, requirement, and behavior. No redundancy, front-loaded with the most important information. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is adequate for a read-only query tool but lacks detail on output structure (e.g., exact fields of audit event objects, pagination details). Without an output schema, more specificity would improve completeness.

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?

Schema coverage is 100% with detailed parameter descriptions. The tool description does not add additional parameter-specific meaning beyond what the schema already provides, so baseline 3 is appropriate.

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 'Query the ClickUp audit log (who did what, when)' with specific filtering capabilities (event type, user, date range). It distinguishes this tool from siblings by naming a unique resource (audit log) not present in other tools.

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?

Mentions Enterprise plan requirement, v3 cursor pagination, and sourcing IDs from other tools (clickup_workspace_list, clickup_member_list). While there is no explicit 'when not to use' guidance, the context around prerequisites 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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