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Glama

Zendesk

by io.github.pipeworx-io

Zd Get User

zd_get_user
Read-onlyIdempotent

Get a Zendesk user by ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUser ID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
userNoUser details

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "user": {
+      "description": "User details",
+      "properties": {
+        "created_at": {
+          "description": "Creation timestamp",
+          "type": "string"
+        },
+        "email": {
+          "description": "User email",
+          "type": "string"
+        },
+        "id": {
+          "description": "User ID",
+          "type": "number"
+        },
+        "name": {
+          "description": "User name",
+          "type": "string"
+        },
+        "role": {
+          "description": "User role",
+          "type": "string"
+        },
+        "updated_at": {
+          "description": "Last update timestamp",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    }
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": 98765
+  }
+]
  3. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds no additional behavioral context (e.g., error cases, permission requirements). It neither contradicts nor enriches the 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 a single, complete sentence. It is concise, front-loaded, and has no unnecessary words. Every word earns its place.

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?

Given the tool's simplicity (one parameter, no nested objects, output schema exists), the description is mostly complete. However, it could mention that the user is returned in the response, but since an output schema is present, this is not strictly necessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage, describing the 'id' parameter as 'User ID'. The description adds no further meaning beyond what the schema already provides, so baseline score 3 applies.

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 is specific: 'Get a Zendesk user by ID.' It clearly states the verb (Get), resource (Zendesk user), and scope (by ID). This distinguishes it from sibling tools like zd_list_users (list all users) and zd_search_tickets (search tickets).

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

Usage Guidelines3/5

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

The description gives no explicit guidance on when to use this tool versus alternatives. Usage is implied: use when you have a specific user ID and need a single user. No exclusions or alternative tools are mentioned.

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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TDQS

B3.3/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the Pipeworx query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim) which all provide factual answers, making it unclear which to use. The set also mixes Zendesk tools with a large number of prediction market and data tools, creating confusion.

Naming Consistency2/5

Naming conventions are inconsistent: Zendesk tools use 'zd_' prefix, Pipeworx tools use various prefixes like 'ask_', 'bet_', 'compare_', etc., and some are named with full words. There is no uniform pattern across the set.

Tool Count2/5

35 tools is high for a server named 'Zendesk', especially since only 5 are Zendesk-specific. The majority are unrelated to Zendesk, indicating the tool count is inappropriate for the implied purpose.

Completeness1/5

For a Zendesk server, the tool set is severely incomplete, offering only basic CRUD operations (get, list, search for tickets and users). Missing essential Zendesk features like ticket creation, update, delete, or macros, while containing many irrelevant tools from other domains.

Resources