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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safe-read profile is covered. The description adds useful return-shape context (thumbs up/down ratings, comments, feedback types) but says nothing about pagination, ordering, volume limits, or what an empty result means. Given the annotation coverage, this is adequate but not rich.

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?

Three short sentences, front-loaded with what the tool returns and followed by filter behavior. No filler, though the middle sentence largely enumerates fields the schema could imply.

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 no output schema, the description usefully characterizes the return contents, and the 100%-covered schema handles parameters. The remaining gap is routing guidance among the many list_* and feedback-related siblings, which an agent may still have to infer.

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 100%, so all four parameters including the feedbackType enum and the customerId superadmin caveat are already documented in the schema. The description restates that optimizationId and feedbackType are optional filters, adding no syntax or format detail beyond the structured fields. Baseline 3 applies.

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?

States a specific verb and resource ("List feedback entries for an agent") and enumerates the returned fields. It implicitly separates itself from the sibling mutators add_optimization_feedback and add_insight_feedback by being the read side, but it never names those siblings or explicitly contrasts listing vs. adding.

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?

"Optionally filter by optimization ID or feedback type" gives minimal guidance on narrowing results, but there is no statement of when to use this tool versus get_optimization_details, get_insights, or the add_* feedback tools. Usage is only implied by the tool name.

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