zendesk_add_ticket_commentMUTATING: add a comment to a ticket. public defaults to true (a reply visible to the requester); set it false for an internal agent note. Convenience over PUT /tickets/{id}.json.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Numeric ticket id (required). | |
| body | Yes | Comment text (required). | |
| public | No | Public reply (true, default) or internal note (false). |
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 have destructiveHint=true, and the description adds 'MUTATING' to reinforce the mutation. It also discloses the default behavior of `public` and the mapping to the REST API, which exceeds annotation coverage. No contradictions.
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 sentences, front-loaded with the operation, and uses compact phrasing that earns its place. No filler 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?
For a simple 3-parameter mutation tool with no output schema, the description covers purpose, public behavior, and API relationship. Missing return value or permission details, but annotations compensate for safety; adequate for the complexity.
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?
Schema covers 100% of parameters with descriptions for id, body, and public. The description only restates the public default that's already in the schema, so it adds no new semantic value beyond structured data.
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?
Clearly states 'add a comment to a ticket' with a specific verb and resource. Distinguishes from sibling tools by clarifying the `public` flag and being a convenience wrapper over PUT /tickets/{id}.json, so it's not confused with update_ticket or create_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?
Provides context about the public flag default and internal note option, but doesn't explicitly name sibling tools or state when to prefer this over update_ticket/list_ticket_comments. The API convenience mention is implicit guidance but not a clear alternative.
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.