log_outcome

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals a core behavior: the new path records an 'interpretation-free' fact, while the legacy path updates Q-values. It also hints at state mutability ('resolve a prediction' and 'updating Q-values'). However, it does not mention side effects like whether the prediction is marked resolved, idempotency, or error handling. Still, it covers the most critical behavioral distinction (new vs legacy) clearly.

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 two sentences (with a dash for emphasis) and front-loads the primary purpose. Every clause earns its place: the purpose, the two-path distinction, the key parameters per path, and the coexistence note. There is zero fluff; it is both concise and information-dense.

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 has 7 parameters, one required, and no output schema, the description provides enough context for an agent to know how to call it: it explains both paths and the necessary parameters. It does not describe the return value or side effects beyond Q-updates, but that information is not strictly required for correct invocation. The coverage is strong for the dominant usage cases, so a 4 rather than a 5 is appropriate.

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 each parameter is already described. The description adds critical usage semantics by mapping parameters to paths: it tells the agent that actual_signal and days_to_resolve are the new-path requirements, while outcome and reward belong to the legacy path. This goes beyond the schema, which only marks parameters as deprecated, and clarifies when to use what, so the added value justifies a score above the baseline of 3.

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 opens with a clear verb-resource pair: 'Resolve a prediction with observed facts.' It explicitly identifies the tool's function and differentiates itself from the sibling log_prediction (which creates predictions) by focusing on resolution. It also distinguishes two execution paths (new vs legacy), making its scope unambiguous without needing to inspect the schema.

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 explicit when-to-use guidance for each code path: 'New path: provide actual_signal and days_to_resolve' and 'Legacy path: provide outcome + reward to keep updating Q-values.' It also notes that the two paths can coexist, preventing confusion about exclusivity. This directly tells an agent which parameters to use in which situation, exceeding minimal guidance.

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