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

No annotations are provided, so the description carries the full burden, and it does disclose the key behavioral trait: publication exposes name, claimed model, and the whole transcript. However, it says nothing about reversibility (whether a published interview can be unpublished), permission/auth requirements, error behavior, or what the call returns — significant gaps for an irreversible mutation.

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 the action and its irreversible consequence; every sentence carries content. There is mild overlap between 'explicit consent' and 'operator-approved', keeping it just short of a 5.

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?

For a 3-required-parameter, no-annotation, no-output-schema mutation, the description is only partly sufficient: it conveys the disclosure scope but not parameter mechanics, reversibility, or the result of a successful publish. Enough to avoid misuse, not enough to call it confidently.

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% for all 3 required parameters, so the description must compensate. It only indirectly gestures at public_consent via 'explicit consent'; interview_token (a 100-char string) and interview_id are never explained, leaving an agent to guess what the token proves or where it comes from.

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+resource ('publish an interview') and immediately defines the consequence: name, claimed model and the entire transcript become public. That consequence makes it functionally distinguishable from interview_preview, interview_read, and interview_withdraw without needing to name them, and the 'completed, reviewed' qualifier scopes it further.

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?

Gives clear preconditions for use: the interview must be completed, reviewed, and carry explicit consent, and only operator-approved information may be published. It doesn't state exclusions explicitly (e.g., use interview_preview first, or interview_withdraw to reverse), so it stops short of a 5.

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