DeskCrew

search_kb

Read-only full-text search over this tenant’s PUBLISHED knowledge-base articles (playbooks, policies, how-tos); unpublished drafts are never returned and the tenant is fixed by your credentials. Reach for this FIRST to ground an answer in official, tenant-specific guidance before replying to a customer or drafting a resolution. Returns articles ranked by relevance, each with its id, title, a highlighted snippet, and updatedAt: search uses AND semantics, so every word in the query must match. [free]

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Optional. Maximum number of ranked articles to return, 1–20. Defaults to 10 when omitted.
`query`	Yes	The search phrase. Uses AND full-text semantics: EVERY word must appear in an article to match, so keep it to the key terms (e.g. "refund policy" or "reset password"), not a full sentence. Comes from the user's question or the topic you need to ground your answer in.

TDQS

A4.8/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses read-only nature, AND search semantics, fixed tenant based on credentials, and that drafts are excluded. Lacks details on rate limits or error behavior but covers key 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?

Two sentences plus a short fragment, front-loaded with purpose. Every sentence adds value: 'Read-only full-text search...' immediately conveys function, then scope, then usage advice. No wasted words.

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, description covers return fields (id, title, snippet, updatedAt) and ranking by relevance. Constraints like limit range and AND semantics are explained. For a 2-parameter tool, this provides all necessary context for correct invocation.

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

Parameters5/5

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

Schema coverage is 100%, but description adds significant meaning: explains AND semantics, recommends keeping query to key terms, and specifies default limit (10) which is not in schema. This helps the agent use parameters effectively.

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?

Clearly states it's a read-only full-text search over PUBLISHED knowledge-base articles, distinguishing it from sibling tools like search_tickets. The description explicitly mentions the scope (tenant-specific, published only) and purpose (ground answers in official guidance).

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

Usage Guidelines5/5

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

Explicitly tells the agent to 'Reach for this FIRST' before replying, and clarifies what it does NOT do (return unpublished drafts). Provides context for when to use it (grounding answers) and implies alternatives for other search needs.

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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