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rlowndes9

Zendesk MCP Server

by rlowndes9

list_ticket_forms

Read-onlyIdempotent

List Zendesk ticket forms with id, name, active status, and field IDs. Supports pagination, filtering, and verbose details for audit.

Instructions

Returns ticket forms as paginated skeletons (id, name, active, default, ticket_field_ids, updated_at). Default limit: 100; pass cursor, fields, filter, or verbose: true. For "is it safe to retire this form?" call find_form_usage, it scans triggers, automations, macros, and views for references. Form lists are typically tiny (single digits to dozens), so straight enumeration is usually fine.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax items to return. Default 100. The full corpus is fetched and cached server-side; this only limits what the response carries.
cursorNoOpaque pagination token from a previous response. Slices the next page from the cached corpus. Stale cursors (older than the cache TTL) auto-reset to offset 0 and set cursor_invalidated: true.
fieldsNoWhitelist of field names. Overrides the default projection. Use to opt into extra fields (e.g. ["id","title","active","position","category_id","updated_at"]) without going fully verbose.
filterNoStructured filter applied to the cached corpus before slicing. Supported keys: active (bool), category_id (number/string), title_contains (string, case-insensitive), updated_since (ISO timestamp). Unsupported keys are ignored with a note in the response.
refreshNoBypass cache and re-fetch from Zendesk
verboseNoReturn full ticket-form objects instead of the thin projection
instanceNoOverride the sticky instance for this call
Behavior5/5

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

Annotations provide readOnlyHint, openWorldHint, idempotentHint. The description adds significant behavioral context: pagination via cursor and limit, caching behavior (server-side cache, stale cursor auto-reset), default projection, optional fields parameter, filter capabilities, and refresh option. No contradictions with annotations.

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 two sentences, front-loaded with core functionality and a bolded usage tip. Every clause adds value: no filler. Efficient and well-structured.

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?

Given no output schema, the description explains the return shape (skeletons with specific fields), pagination, caching, filtering, projection options, and typical list size. It covers all essential aspects for an agent to use the tool correctly.

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%, so baseline is 3. The description adds meaning beyond schema: e.g., 'Default limit: 100', cursor caching details, filter supported keys, and the effect of verbose vs. fields. This enriches understanding of parameters without repeating schema.

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 it returns ticket forms as paginated skeletons with a specific projection (id, name, active, etc.). It distinguishes from the sibling tool 'find_form_usage' by its use case: enumeration vs. safety checking. The verb 'Returns' and resource 'ticket forms' are specific.

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 explicitly says when to use this tool vs. the alternative: 'For "is it safe to retire this form?" call find_form_usage'. It also notes that 'straight enumeration is usually fine' due to small form lists. However, it could be clearer about when not to use this tool (e.g., if you need full details without verbose).

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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