DeskCrew

list_tickets

Read-only: list support tickets in the caller's tenant, sorted by most recent message first. Reach for this to discover ticket ids, triage the queue, or poll for activity before acting on a specific ticket; results can be narrowed by status, priority, assignee, and an updated-since timestamp, and capped via limit (max 50, default 20). Returns lightweight ticket summaries (id, subject, status, priority, lastMessageAt, customer, assignee, tenant) plus the total match count: it never creates or modifies anything. [free]

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Optional maximum number of tickets to return, an integer from 1 to 50. Defaults to 20 when omitted. Results are sorted by most recent message first.
`since`	No	Optional filter: only return tickets updated at or after this time. An ISO-8601 UTC timestamp (e.g. "2026-06-28T00:00:00Z"). Use this to poll for recently active tickets.
`status`	No	Optional filter: only return tickets in this status. One of 'active', 'pending', 'snoozed', or 'closed'. Omit to include all statuses.
`priority`	No	Optional filter: only return tickets at this priority. One of 'low', 'normal', 'high', or 'urgent'. Omit to include all priorities.
`assigneeId`	No	Optional filter: only return tickets assigned to this agent. Pass the agent id (e.g. from a ticket returned by this tool). Omit to include tickets regardless of assignee.

TDQS

A4.7/5.0

Behavior5/5

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

Read-only and non-destructive behavior is explicitly stated ('never creates or modifies anything'). Returns lightweight summaries with specific fields and total count, sorted by most recent message. With no annotations, this fully discloses behavioral traits.

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?

Description is concise and well-structured: read-only flag first, then use cases, then filtering options, then return format, then safety guarantee. Every sentence is informative with no waste.

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 covers the return values (lightweight summaries with specific fields). It also explains sorting, limits, and filtering, making it complete for a list tool.

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% with descriptions for each parameter, so baseline 3. The description adds value by explaining the default and max for limit, and the purpose of filters (e.g., 'poll for recently active tickets'). Slightly above baseline.

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 'list support tickets' with a specific verb and resource, and distinguishes from siblings like search_tickets by focusing on listing vs searching. It also notes the sorting order.

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?

Provides explicit use cases: 'discover ticket ids, triage the queue, or poll for activity'. While it doesn't directly say when not to use, the context and sibling tools imply alternatives. Could be improved by contrasting with search_tickets.

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

A4.4/5.0

Disambiguation4/5

Most tools have distinct purposes, but the presence of three drafting tools (draft_reply, draft_support_reply, propose_resolution) with overlapping functionality may cause confusion. Descriptions help differentiate them, but an agent could still misselect.

Naming Consistency4/5

Tool names predominantly follow a verb_noun pattern in snake_case (e.g., create_ticket, list_issues). However, a few tools like 'assign' and 'triage' are single verbs, and 'draft_support_reply' breaks the pattern slightly. Overall consistent but not perfect.

Tool Count5/5

16 tools is well-scoped for a customer support server covering ticket management, issue tracking, knowledge base, and changelog. Each tool serves a clear purpose without bloat.

Completeness4/5

The tool surface covers the core ticket lifecycle (creation, triage, assignment, context, drafting, sending, resolving) and supports issue linking and knowledge base search. Minor gaps like updating ticket details or bulk actions exist but are not critical.

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