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rlowndes9

Zendesk MCP Server

by rlowndes9

get_ticket_audits

Read-onlyIdempotent

Retrieve the audit history of a Zendesk ticket to trace state changes, identify rule attributions, and debug unexpected macro or trigger behavior.

Instructions

Returns the audit history for a ticket, every state change with rule attribution and event timestamps. Defaults to limit: 100 events; pass since to bound by date, event_types: ["Change"] to skip Comment events entirely (much smaller response). Scope-gated, requires config_plus_audits or full; at config_plus_audits Comment-event bodies are auto-redacted. Use this for forensic debugging ("why did this macro send the ticket to the wrong group?"), via.source on each audit names the trigger / macro / app that made the change. For pure timing data, get_ticket_metrics is cheaper.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesTicket ID
limitNoMax audit events to return. Default 100. Audits on noisy tickets can run to thousands of events.
sinceNoISO timestamp. Only return audits with created_at >= since. Useful for "what changed today" queries.
cursorNo
fieldsNo
filterNo
refreshNoBypass cache and re-fetch from Zendesk
verboseNoReturn full audit objects instead of the thin projection
instanceNoOverride the sticky instance for this call
event_typesNoFilter audit.events to only these types. Common: ["Change"] to skip Comment events entirely. ["Change","Notification"] to include rule notifications.
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. Description adds crucial details: defaults to limit:100, event_types filtering, scope-gated behavior with auto-redaction of comment bodies, and via.source attribution. No contradiction.

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?

Single paragraph with front-loaded purpose, then defaults, filtering, scope, use case, and alternative. Every sentence adds value; no wasted words.

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?

Complex tool with 10 params and no output schema. Description covers core behavior, use case, permissions, and parameter usage. Lacks explanation of cursor pagination and filter object, but overall sufficient for agents.

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 70%. Description adds meaning for limit (defaults to 100), since (bound by date), and event_types (skip Comment events). Also implies verbose returns full objects. Compensates for undocumented parameters like cursor and filter.

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?

Description states it returns audit history for a ticket with state changes, rule attribution, and timestamps. Clearly distinguishes from sibling get_ticket_metrics by noting different use cases. Specific verb+resource+scope.

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?

Explicitly advises 'Use this for forensic debugging' with example question, and notes alternative 'For pure timing data, get_ticket_metrics is cheaper'. Also mentions scope requirements and filtering options.

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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