freeze label set

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

Discloses important behaviors beyond annotations: re-freezing re-measures kappa but preserves original frozen_at and membership, kappa is null rather than 'good' when insufficient raters exist, 400 is returned when inter-rater stats are unavailable, and the endpoint requires evals:write scope. This is rich, honest behavioral context.

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?

Front-loaded with the core purpose, then organized into endpoint, response shape, and edge-case notes. Every sentence carries useful information; there is 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?

With no output schema, the description fully compensates by enumerating the complete returned object and its field types. It also covers idempotency nuances, null semantics, and error conditions, making the tool's behavior fully understandable for an agent.

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% and the id parameter is already documented as workspace-scoped with a 404 case. The description adds the endpoint path and no-body requirement, but does not substantially expand parameter meaning beyond the schema.

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 and resource: freeze a golden set, seal membership with a hash, and measure inter-rater agreement (kappa). The unique behavior clearly distinguishes it from sibling label-set tools like create_label_set or attach_label_set.

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 clear context by saying freezing is required before a judge can calibrate on the set, and explains re-freezing behavior. It does not explicitly name alternatives or state when-not-to-use, but the usage context is unmistakable.

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