athena_antibody_record_outcome

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 states the action (recording) but does not disclose side effects, prerequisites (e.g., whether the antibody must be pre-registered), idempotency, error behavior, or what the tool does on duplicate records. For a mutation tool, this is a significant gap.

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 a single concise sentence that efficiently conveys the tool's purpose and enumerates the outcome types. No redundant information or filler words are present.

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 annotations, no output schema, and sparse parameter descriptions, the description is insufficient for effective use. It does not explain what a 'known failure antibody' is, what the function returns, how to identify the antibody, or whether prior registration is needed. The existence of sibling tools like athena_failure_antibody_register hints at a workflow, but this is not addressed.

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%. The description adds meaning for two parameters: 'outcome' (listing valid values) and 'antibody_id' (implied by 'known failure antibody'). However, the 'actor' parameter is not explained at all, leaving it ambiguous. The description partially compensates for the lack of schema descriptions but not fully.

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 a specific action ('Record') and resource ('outcome for a known failure antibody'), and enumerates the exact types of outcomes (success, failure, false positive, regression pass, regression failure). This distinguishes it from siblings like athena_failure_antibody_register or athena_antibody_evolve, which have different purposes.

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 gives a clear usage context: it is for recording outcomes specifically for 'known failure antibodies.' It does not explicitly name alternatives or exclusions, but the phrase 'known failure antibody' implies it should be used when such an antibody exists, effectively distinguishing it from registration or selection tools.

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