Skip to main content
Glama
rlowndes9

Zendesk MCP Server

by rlowndes9

list_skills

Read-onlyIdempotent

Resolve a Zendesk routing attribute named 'skills' and return its values as skeletons. Supports attribute ID or name, filtering, and pagination.

Instructions

Convenience wrapper that resolves a "skills"-like routing attribute and returns its values as skeletons. Pass attribute_id to target one specifically, or attribute_name (case-insensitive; defaults to "skill"/"skills"). Modern Zendesk has no /skills.json endpoint, this tool exists because LLMs ask for "skills" by name; under the hood it's list_routing_attribute_values against the skill attribute. Plan-gated. For agent assignments use list_agent_skill_assignments.

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
verboseNoReturn full value objects
instanceNoOverride the sticky instance
attribute_idNoSpecific routing attribute ID to enumerate as skills
attribute_nameNoMatch an attribute by name (case-insensitive). Default: matches "skill" or "skills".
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds context about being a convenience wrapper and plan-gating, but does not disclose caching behavior or other implicit traits beyond what is already in the structured fields.

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 4 sentences, front-loaded with the purpose, and every sentence adds value: purpose, parameter guidance, rationale, and alternative tool. 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?

Given 9 parameters, 100% schema coverage, and no output schema, the description provides sufficient context—purpose, key parameters, alternative, and plan restriction. It mentions 'skeletons' which hints at the output, but could be more explicit about return structure. Still, it is complete enough for most agents.

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?

Schema description coverage is 100%, so baseline is 3. The description adds minimal extra meaning beyond the schema, e.g., emphasizing case-insensitivity and defaults for attribute_name, but these are largely already captured in the parameter descriptions.

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 the tool is a convenience wrapper that resolves a 'skills'-like routing attribute and returns its values as skeletons. It specifies the key parameters (attribute_id and attribute_name) and distinguishes itself by explaining it exists because LLMs ask for 'skills' by name, with an explicit alternative (list_agent_skill_assignments).

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 says 'For agent assignments use list_agent_skill_assignments' and notes the tool is plan-gated, providing clear when-to-use guidance. It also hints at the underlying mechanism (list_routing_attribute_values) but does not explicitly state when to prefer this tool over list_routing_attribute_values.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rlowndes9/zendesk-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server