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

The annotations already declare readOnlyHint=true and destructiveHint=false. The description goes beyond this by adding: 'Read-only, 0 credits,' which reinforces safety and adds cost clarity. It also discloses internal decision rules: suppression below 5 measured posts, no cross-channel comparisons, untried hooks reported as observation not advice, and unusable hooks explained (e.g., on-screen-text hook cannot ride an authentic/UGC render). This is rich, honest behavioral detail that the annotations alone do not provide.

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 front-loaded with the core purpose, but it is quite verbose, running several long sentences with repeated caveats. While all information is relevant, it could be tightened. For example, the three 'will not do' clauses are valuable but could be compressed. It is not pithy, but it is structured logically (purpose, usage, exclusions, read-only note).

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 the tool's complexity (read-only, 4 optional params, no output schema), the description does a strong job of explaining what it returns (hooks+settings+traction), its usage context, and its behavioral constraints. The only gap is a lack of explicit return format/fields, but that is mitigated by the rich description of the menu and performance data. The detailed decision rules make it clear enough for an agent to call 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 description coverage is 100%: each parameter (tier, channel, category, authentic) already has a clear description in the schema. The tool's description does not add any parameter-specific meaning beyond what the schema provides; it focuses on overall behavior and output interpretation. Since the schema does the heavy lifting, a baseline of 3 is appropriate.

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 opens with a specific statement: it is the curated menu of VISUAL scroll-stop HOOKS and SETTINGS that plan_ad and render_ad accept, plus measured traction per hook. This clearly identifies the resource, and the mention of plan_ad/render_ad distinguishes it from sibling tools. The three 'will not do' clauses further sharpen 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 explicitly instructs when to call it: 'Call it before planning an ad to pick a hook deliberately instead of letting the model improvise one, and call it after publishing to see which ones are actually landing.' This gives two concrete trigger times and contrasts with the improvisation alternative. It also states what it will not do (no recommending from thin data, no cross-channel comparison, untried hooks reported as fact), which helps the agent decide when NOT to rely on it.

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