Get reviewed examples

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

No annotations provided; description only states what the tool returns (draft vs. final text, feedback) but omits behavioral traits like whether it is read-only, idempotent, or any permissions needed. Schema adds no behavioral cues.

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?

Two sentences with no redundant information. First sentence states the resource and content; second sentence highlights its primary use. Every word earns its place.

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?

Lacks output schema; description provides a high-level view of returned content (signals, comparison, feedback) but no details on fields or structure. For a 3-parameter optional tool, this is minimally adequate but leaves agents guessing about output format.

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 covers 100% of parameters with descriptions (limit, status, platform). Description does not add extra semantic meaning beyond what the schema already provides, so baseline score of 3 is appropriate.

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?

Description clearly states it retrieves reviewed signals showing draft vs. final text and feedback, and explicitly names it as the primary 'learn from outcomes' source, distinguishing it from sibling tools like feedback_get or signals_get.

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?

Implicitly suggests use for learning from outcomes but does not specify when to use versus alternatives or when not to use. No explicit exclusions or conditions provided.

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