zendesk_get_ticket_metricsFetch SLA / response / resolution time metrics for a ticket. Zendesk REST: GET /tickets/{id}/metrics.json.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Numeric ticket id (required). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds the specific metric types and REST endpoint, but doesn't describe response format or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose, followed by API reference. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter and read-only annotation, the description covers the operation sufficiently, though it could specify the response shape. Slightly above minimum.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'id' is fully described in the schema with type and constraints, so the description adds no new parameter semantics; baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches SLA/response/resolution metrics for a ticket, and the REST endpoint disambiguates from siblings like zendesk_get_ticket.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit alternatives are mentioned, but the focus on metrics makes its use case clear: when ticket metric details are needed. Context is clear but lacks explicit when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but zendesk_search_users overlaps with zendesk_search (which can search users with type:user), and zendesk_update_ticket can also add a comment, overlapping with zendesk_add_ticket_comment. These create minor ambiguity but are clarified by descriptions.
All tools use a consistent 'zendesk_' prefix and snake_case, but naming patterns deviate slightly: zendesk_current_user lacks a 'get_' verb, and zendesk_execute_view uses 'execute' instead of 'list' or 'get'. Overall, the conventions are mostly uniform and readable.
19 tools is on the higher end but each corresponds to a distinct Zendesk API endpoint or operation. The count is well-scoped for a server covering tickets, users, organizations, views, macros, and satisfaction ratings, without excessive redundancy.
The ticket lifecycle is well covered (create, get, update, comment, list, search, metrics, views), and listing entities like orgs, groups, macros, and fields is supported. Minor gaps exist for user/organization updates and a plain list_users tool, but these are not critical for core support workflows.