recommend_content

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

With no annotations, the description carries the full burden. It reveals the ranking factors (watch history, categories, freshness, etc.), giving insight into its operation, but it does not state whether the tool mutates state, requires authentication, or what the output format is. This is modest but incomplete transparency.

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 entire description is a single, front-loaded sentence with no wasted words. It immediately states the action ('Rank') and the resource ('what to watch next'), making it highly concise and well-structured.

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 tool with 11 parameters, no annotations, no output schema, and no guidance on return values or edge cases, the description is too brief. It gives a general sense of purpose but lacks the detail needed for reliable invocation, especially regarding parameter semantics and output handling.

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%, so the description must compensate for 11 parameters. It only hints at a few (categories, freshness, apps) and leaves core parameters like deviceId, limit, catalog, mood, includeSeen, and chatLinkMode unexplained. This is insufficient for an agent to correctly construct a request.

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 clearly identifies the tool as ranking 'what to watch next' using specific inputs like watch history, categories, freshness, apps, and discovered launchability. This distinguishes it from sibling tools like search_content, though it does not explicitly differentiate from suggest_content.

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 implies usage for generating a ranked watch-next list, but it does not provide explicit guidance on when to use this tool versus siblings like suggest_content or search_content, nor list any exclusions or prerequisites.

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