athena_bandit_observe

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

With no annotations, the description must disclose side effects and behavioral traits. It states that the tool updates a posterior and warns 'predictions never train themselves,' but it does not detail persistence, mutability, reversibility, or any necessary permissions. This is insufficient for a mutation-like operation, as the agent cannot infer the full impact of the call.

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 very brief and to the point, with two clauses that communicate the core action and a behavioral warning. It is not verbose, and each phrase contributes some meaning. The cryptic nature of 'predictions never train themselves' slightly reduces clarity, but the overall structure is efficient.

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 tool's complexity (6 params, nested objects, no output schema, no annotations, and no parameter descriptions), the description is far from complete. It does not explain what features or regime represent, how the posterior is represented, or what the result of the update entails. The description provides only a high-level statement, leaving major gaps for the 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?

The schema has 0% description coverage, and the description does not compensate by explaining any of the six parameters. While 'reward' is implicitly mentioned, the meanings of 'arm_id', 'regime', 'features', and 'global_transfer_weight' are left entirely to guesswork. The tool description provides no added value over the raw property names.

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 identifies the tool's function: updating a single regime/action posterior from an explicit observed reward. The phrase 'one regime/action posterior' scopes the operation, distinguishing it from batch or automatic updates, and the mention of 'explicit observed reward' provides a concrete resource and input.

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 implies when to use this tool: when explicit observed rewards are available to update a posterior. The clause 'predictions never train themselves' hints that this is the manual pathway for incorporating observations, but it does not explicitly name alternatives or provide clear 'when not to use' guidance, leaving the usage context somewhat implied.

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