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

No annotations are provided, so the description carries full burden — and it excels: it discloses that boilerplate is discounted automatically, that 'none' verdict means the corpus genuinely lacks coverage, that strong results include root causes with cheap checks, and that partial results are only leads. This goes far beyond a simple 'lookup' statement.

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?

Four sentences, each earning its place: the first defines the tool, the second covers input flexibility, the third explains the verdict semantics and its implication, and the fourth gives actionable next steps. Front-loaded with the primary purpose; no fluff 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?

Given the modest schema (2 params, no output schema) and sibling context, the description fully equips an agent to call it correctly and interpret the result. It covers input format, output verdicts, edge case behavior ('none'), and the follow-up action — nothing essential is missing for correct invocation and use.

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%, so the schema already documents both parameters. The description adds meaningful context about the 'error' parameter by suggesting it accepts messages, codes, or stack traces and that boilerplate is auto-filtered — exceeding what the schema's one-line description provides. The 'limit' parameter is implicit but not explicitly detailed, a minor gap.

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 states a specific verb ('Find') and resource ('verified, source-backed entries for a concrete technical error') and clearly distinguishes this from siblings like knowbase_diagnose by positioning it as an initial lookup step. The scope is explicit: returns only strong/partial/none verdicts, not the nearest entry.

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?

Explicitly tells the agent when to use it ('Paste the error message, error code, or the whole stack trace'), what to expect (verdict types), and what not to do (do not use partial results without an independent match). It also routes to knowbase_diagnose after strong matches, naming the alternative tool and the trigger condition.

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