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Read Audit Log

cascade_read_audits
Read-onlyIdempotent

Retrieve Cascade CMS audit log entries with filters for user, date, action type, and asset. Supports pagination to navigate through results.

Instructions

Read Cascade audit log entries matching the specified filters.

Queries Cascade's system audit log for events like edits, publishes, logins, check-outs, deletes, and workflow transitions. All auditParameters fields are optional — providing none returns every recorded event (expect large volumes; always apply a date range filter). Results are always returned newest-first by Cascade; this MCP layer then slices the page.

Args:

  • auditParameters (object, required, shape varies — see Cascade docs): Filter conditions

    • identifier (object, optional): Limit to events on a specific asset

    • username (string, optional): Limit to events by a specific user

    • groupname (string, optional): Limit to events by users in a group

    • rolename (string, optional): Limit to events by users with a role

    • startDate (string, optional): ISO-ish date; earliest event to include

    • endDate (string, optional): ISO-ish date; latest event to include

    • auditType (string, optional): One of: "login", "login_failed", "logout", "start_workflow", "advance_workflow", "edit", "copy", "create", "reference", "delete", "delete_unpublish", "check_in", "check_out", "activate_version", "publish", "unpublish", "recycle", "restore", "move"

  • limit (number, optional): Max results per page, 1-500 (default 50)

  • offset (number, optional): Skip N results for pagination (default 0)

Returns: The response is a page: { success: true, total: , count: , offset: , has_more: , next_offset: <offset for next page, if has_more>, audits: [ { user, action, identifier?: { ... }, date }, ... ] } On failure: { success: false, message: "" }

Examples:

  • Use when: "Who edited /about today?" -> { auditParameters: { identifier: { type: "folder", path: { path: "/about", siteName: "www" } }, auditType: "edit", startDate: "2026-04-13T00:00:00Z" } }

  • Use when: "All logins in April 2026" -> { auditParameters: { auditType: "login", startDate: "2026-04-01T00:00:00Z", endDate: "2026-04-30T23:59:59Z" } }

  • Don't use when: You want the current state — use cascade_read.

  • Don't use when: You want user inbox messages — use cascade_list_messages.

Pagination:

  • Default limit of 50 works for most queries. Increase up to 500 for larger pages.

  • If has_more is true and you need all audits, call again with offset: next_offset.

  • For a complete enumeration (e.g., all audits in a date range), loop until has_more: false.

  • For focused queries where you only need the most recent, stop as soon as you have what you need.

Error Handling:

  • "Invalid date format" when startDate/endDate don't parse

  • "Invalid auditType" when auditType isn't in the allowed set

  • "Permission denied" when credentials lack audit-read rights. Responses are JSON text; structuredContent is authoritative when the response fits. Oversized responses return bounded _cache metadata for cascade_read_response. For cascade_read, read_mode controls preview versus raw Cascade payload shape.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
auditParametersNoREQUIRED: Audit filters (identifier, username, groupname, role, auditType, start/end dates). Matches Cascade's AuditParameters shape.
limitNoMaximum results per page (default: 50, max: 500). Check has_more and use next_offset to iterate. For a complete enumeration, loop until has_more=false.
offsetNoSkip this many results for pagination (default: 0). Use with limit + has_more to iterate through large result sets.
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds significant behavioral context: results are always newest-first, all filter fields are optional, default limit is 50, max 500, pagination via has_more/next_offset, error handling for invalid dates, audit types, and permission denied. This goes well beyond the annotations without contradiction.

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 structured with clear sections (Args, Returns, Examples, Pagination, Error Handling) and front-loaded with purpose. It is verbose but every section adds value. Minor repetition (e.g., error handling mentions cascade_read_response boilerplate) prevents a 5, but it remains well-organized and informative.

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?

Despite no output schema, the description provides a sample return structure (success, total, count, offset, has_more, next_offset, audits) with field descriptions. It covers pagination loops, error scenarios, and example queries. For a read operation with filter complexity, this is comprehensive and leaves little ambiguity.

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 coverage is 100% with detailed descriptions for each parameter. The description adds value by explaining the meaning of auditParameters fields more contextually (e.g., allowed values for auditType, optional nature) and clarifying pagination behavior. While the schema covers syntax, the description enhances semantic understanding.

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 'Read Cascade audit log entries matching the specified filters.' It clearly identifies the verb 'Read' and resource 'audit log entries.' The tool name 'cascade_read_audits' reinforces this. The description further distinguishes from siblings like 'cascade_read' (current state) and 'cascade_list_messages' (user inbox) through explicit 'Don't use when' notes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit 'Use when' examples (e.g., 'Who edited /about today?') and 'Don't use when' alternatives ('use cascade_read', 'use cascade_list_messages'). It also advises on when to apply date range filters to avoid large volumes, giving clear contextual guidance.

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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