assess_misconception

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

There are no annotations, so the description carries the full burden of behavioral disclosure. 'Record ... in its authoritative table' implies a durable write operation, but it does not explain whether the record is created or updated, whether it is idempotent, what side effects occur, or what the return value is. This is thin for a mutation tool.

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 front-loaded sentence with no filler or redundant phrasing. It is genuinely concise, though the brevity contributes to gaps in behavioral and parameter detail.

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 six parameters, no annotations, and no output schema, this description is contextually incomplete. It does not clarify how this tool relates to resolve_misconception, how severity is interpreted, or how request_id/session_id participate in the operation, leaving an agent to guess important calling details.

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 does not explain any of the six parameters. The names learner_id, node_id, and misconception are self-explanatory, but severity's scale/range, the purpose of request_id/session_id, and the expected format of misconception are left entirely to inference.

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 states a specific verb ('Record') and a specific resource ('an active misconception' in its 'authoritative table'), so an agent can understand the core operation. However, it does not distinguish itself from closely related sibling tools such as resolve_misconception or assess_response.

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 intent is implicitly clear: use this when an active misconception needs to be recorded. There is no explicit guidance about when to prefer a sibling tool, nor any exclusion criteria, so usage context is only implied rather than stated.

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