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

The description directly contradicts the annotations. The annotations declare 'readOnlyHint: false', implying the tool may modify data, but the description states 'never changes the KG' (knowledge graph). Additionally, the description mentions 'does not trigger search or an LLM call,' which is useful behavioral context, but the contradiction about mutability is a severe inconsistency that could mislead an agent into thinking the operation is safe when the annotation flags otherwise.

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 concise yet information-dense, spanning three sentences without redundancy. It begins with the core action, then specifies inheritance and non-mutability, and ends with usage criteria and exclusions. The structure effectively front-loads critical information while avoiding unnecessary elaboration.

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?

The description covers many necessary aspects, such as when to use, exclusions, and the non-search behavior, and the schema handles parameter details. However, the contradiction about modifying the knowledge graph severely undermines completeness because an agent cannot rely on the described behavior versus the annotation. This inconsistency creates ambiguity about the tool's actual side effects, making it incomplete for reliable decision-making.

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?

All 7 parameters are documented with 100% schema coverage. Required parameters feedbackId and body have clear descriptions: feedbackId is 'The public feedback id returned by the feedback list or a previous feedback action,' and body is 'One short, lawful reply' with length constraints. Optional parameters like language and feedbackType benefit from enums and explanations, making selection unambiguous.

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 tool's function: 'continue a relevant public discussion by replying to one feedback id.' It specifies the resource (feedback) and the action (reply), and explicitly distinguishes itself from siblings like list_feedback (listing) and submit_agent_feedback (submitting) by emphasizing it continues an existing discussion. The mention of 'inherits the original entity, topic, or section target' further clarifies its scope.

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 provides explicit when-to-use guidance: 'Prefer this when interactionContract or list_feedback finds a relevant thread.' It also states exclusions: 'Skip discovery-only requests and do not repeat the same message,' and clarifies that it does not trigger search or an LLM call, which helps agents decide between this and other tools like search_knowledge_graph.

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