company_kb_search

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

No annotations are provided, so the description carries the full burden. It discloses scope ('synchronized') and output behavior ('ranked snippets with stable GitLab citations'), and the verb 'search' implies a read-only operation. It does not address auth, rate limits, or no-result behavior, but those are less critical for a read-oriented search tool.

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-load the action, resource, and output type, then immediately give usage examples. Every word earns its place with no filler or repetition.

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?

An output schema exists, so return-value details are supplied structurally. The description covers scope, use cases, and output style, which is enough for basic usage; the main gap is unexplained optional parameters like filters and searchMode.

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 description coverage is 0%, and the description only clarifies the query concept via the tool's purpose. It never explains limit, filters, or searchMode; 'hybrid' in particular is ambiguous, and filters has no structural constraints to help an agent infer valid values.

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?

States a specific verb ('Search') over a specific resource ('synchronized company Markdown documentation') and describes the output ('ranked snippets with stable GitLab citations'). It distinguishes itself from siblings like company_kb_answer and company_kb_open_doc by framing this as discovery/evidence gathering rather than direct answering or opening a single doc.

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 explicit use cases: 'discovery questions, finding runbooks, locating ADRs, or collecting evidence before answering.' It does not explicitly name alternatives or when-not-to-use conditions, but the 'before answering' phrasing implies a boundary with company_kb_answer.

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