knitbrain_record_false_positive

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

Discloses threshold adjustment behavior after 3 same-direction reports, which is key behavioral insight beyond just recording. No annotations provided, so description carries full burden and handles it well.

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, no redundancy. First sentence captures purpose, second adds behavioral context. Efficient and well-structured.

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?

For a simple tool with no output schema and straightforward parameters, the description provides all necessary context: what it does, how it works, and its impact. No gaps.

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 already covers all parameters with enums and descriptions. Description reiterates the core mapping (claimed vs actual) but adds no new semantic meaning beyond that. Baseline 3 is appropriate.

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?

Clear verb+resource: 'record false positive' from a classifier. Distinguishes from sibling tools like knitbrain_classify_task and knitbrain_record_learning by focusing on misclassifications.

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?

Context is clear: use when classifier is wrong. Implicitly excludes other scenarios. Does not explicitly state when not to use, but sufficient for the simple purpose.

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