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

No annotations are supplied, so the description carries the full behavioral burden and largely fails it. Beyond the vague claim that it produces "a prompt and operating playbook," it says nothing about output shape, length, whether it acts on data or just returns static guidance, or any preconditions — and the schema's mention of scoping "analysis" is not reconciled with the "prompt toolkit" framing.

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?

Only three sentences, but the lead sentence ("Save hours every week") is pure marketing padding placed where the operational statement should be. The front-loading is spent on sales copy instead of on what the tool does or when to call it.

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 tool is structurally simple — one optional parameter, no output schema, no nested objects — so the bar is low, yet the description still leaves the essential question unanswered: what does invoking it actually produce and in what form? The "works in any LLM chatbot" line reads like promotional boilerplate and does not close that gap.

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?

There is a single optional parameter with full schema description coverage, so the schema already defines `query` adequately. The description adds nothing about how the query scopes output, but with 100% coverage the baseline of 3 applies rather than a penalty.

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 sells the tool ("Save hours every week", "battle-tested") rather than stating a concrete operation. It hints that the tool returns "a prompt and operating playbook for restaurant/brand growth," which is more than a restatement of the name, but it never says what the agent actually gets back or how video idea planning is performed, and it does not distinguish itself from the many sibling video/short-video script and topic tools.

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?

There is no guidance on when to use this tool versus alternatives, despite a crowded sibling set including short-video-script, viral-topic-miner, video-shot-script-master, and campaign-idea-generator. "No setup, works in any LLM chatbot" is a product claim, not a usage condition, and "restaurant/brand growth" is too loose to route an agent reliably.

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