extract_inference_trace

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

Annotations are all false and provide little safety or read-only context, so the description carries the burden. It only says 'extract evidence' and does not disclose what boundedness means, what 'prompt-free' implies, whether there are side effects, or how the evidence is returned. There is no contradiction with the annotations, but the behavioral disclosure is minimal.

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 one dense sentence with no filler and the core verb is front-loaded. It is concise, though the heavy use of unexplained jargon slightly reduces accessibility.

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 one required parameter and an output schema, the tool is not highly complex, but the description leaves key context undefined: what a 'Mooncake request schedule' is, what 'bounded' and 'prompt-free' mean, and how this tool fits into the extraction workflow. An agent selecting among dozens of sibling tools would need more context.

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% and the description never mentions run_id. The single parameter is a simple string whose meaning is partially inferable from its name and schema title, but the description fails to explain how run_id relates to the extraction, so it does not compensate for the lack of parameter documentation.

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 names a specific verb ('Extract') and a distinctive resource ('Mooncake request schedule evidence'), which helps separate it from the many sibling extract_* tools. However, the qualifiers 'bounded' and 'prompt-free' are unexplained jargon, so the purpose is clear but not fully transparent.

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 versus alternatives, and there are no exclusions or contextual cues. An agent is left to guess whether extract_inference_trace is preferred over extract_observations, extract_inference_result, or get_extraction.

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