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

The annotations already cover read-only, idempotent, non-destructive, and closed-world safety. The description usefully adds that each part cites its sources, that figures are published ranges rather than income promises, and how matching works for the optional topic. It does not discuss response size or pagination, but adds meaningful context beyond the annotations.

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 resource definition, then explains no-argument and with-argument behavior, then adds sourcing and disclaimer notes. The parenthetical enumeration of fourteen playbook topics is long but informative; it slightly burdens conciseness without being redundant.

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?

With rich annotations and a fully described single parameter but no output schema, the description still explains the return shape (business model, key facts, takeaways) and directs the agent to get_page for full text. Nothing needed to select or invoke the tool correctly appears to be missing.

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%, so the baseline is 3. The description goes further by clarifying that the optional topic filters matching playbook parts and provides concrete example values such as "clipping", "YouTube pay", and "real estate", adding semantic value beyond the schema's brief field description.

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 names a specific resource—CutLuma's researched guides on earning money with video—and enumerates the covered playbook topics. It clearly distinguishes itself from the sibling get_page by stating that full text is read there, so an agent can tell what this tool returns without opening the schema.

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?

It gives explicit branching: omit the topic argument to get every part with model, key facts, and takeaways; supply a topic to filter matching parts. It also names get_page as the alternative for reading full text. No explicit when-not-to-use condition is provided, so it falls 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.