log-feedback

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

With no annotations, the description solely carries transparency. It only says 'log evaluation feedback' but does not describe mutation semantics (e.g., appending vs overwriting), required permissions, error conditions, or idempotency.

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 front-loads the purpose. It is efficient but could benefit from additional context without being verbose.

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 6 parameters, nested objects, and no output schema, the description is incomplete. It doesn't specify return value, idempotency, or constraints (e.g., traceId must exist). Agents may not know how to handle responses or errors.

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 67% with most parameters described. The tool description adds that the value is a 'score or judgment', which aligns with the schema's 'value' description. No further parameter-level detail 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?

The description clearly states the verb (log) and resource (evaluation feedback) on a trace, distinguishing it from sibling tools like log-metric or log-param. However, it doesn't explicitly differentiate from log-expectation or log-batch, which may cause overlap.

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?

No guidance is given on when to use this tool vs alternatives like log-metric, log-param, or log-expectation. Agents are left to infer based on tool names alone.

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