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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds what they cannot: it is advisory only, never modifies the draft, never blocks scheduling, and it instructs the agent how to handle output (offer topFixes, evaluate needsJudgment itself, never invent facts). That output-handling guidance is genuinely beyond the structured metadata.

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 long but front-loaded: purpose and checklist first, then usage triggers, then behavioral constraints and edge cases. Each sentence carries distinct information, though the checklist enumeration and the trailing instructions could be tightened slightly.

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?

An output schema exists, so return values need no explanation. The description covers the audit scope, when to invoke, the advisory/no-side-effect guarantee, and the published-article edge case — everything an agent needs to call and act on this tool correctly.

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 coverage is 100% and the single draftId parameter is fully documented in the schema ('Article draft id from list_drafts'). The description adds no format, sourcing, or validation detail for the parameter, so the schema does all the work — 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 (audit an article draft for AI search visibility) and enumerates the exact signals it inspects — opening answers, headings, links, sourced figures, lists, alt text, CTA, title length. This makes it immediately distinguishable from siblings like get_draft (retrieval) and update_draft (mutation).

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 explicit triggers — 'call it before scheduling an article' and 'when the writer asks how to make a post easier to find' — plus an explicit alternative for the published-article case ('give the writer revised sections to paste... instead of calling update_draft'). Both when-to-use and when-not-to-use are covered.

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