Search the runbook

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 implies a read-only search operation but does not explicitly state whether the tool modifies anything, what it returns, or any performance characteristics. This is adequate but minimal for a 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?

The description is extremely concise, using two short sentences to convey purpose and usage. It front-loads the core action and immediately adds practical advice, with no wasted words.

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?

With no output schema, the description cannot rely on structured return types. It provides enough context for a simple search tool—what it searches, why to use it, and a high-level example—but lacks explicit detail about the result format or edge cases. This is sufficient for a low-complexity tool.

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 coverage is 100%, with both 'query' and 'limit' already described in the schema. The description adds no additional parameter-level meaning beyond what the schema provides, so it meets the baseline without enhancing understanding.

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?

The description clearly states the tool's verb ('Search') and resource ('the local runbook of known symptoms and their fixes'). It distinguishes itself from sibling tools like tail_log and check_endpoint by focusing on knowledge lookup rather than live system interaction, making its purpose unambiguous.

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?

The description explicitly recommends using this tool before diagnosing an issue from scratch, providing clear guidance on when to invoke it. It does not name alternatives or exclusion scenarios, but the 'before diagnosing' context implies when it should be preferred over other investigation methods.

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