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

The description discloses several behavioral traits beyond annotations: synchronous execution, the DataForSEO envelope structure (data in tasks[0].result, outcome in tasks[0].status_code), the fact that a rejected request still returns HTTP 200, and the measured payload sizes for different result depths. It also warns about the 'html' depth being 2.4 MB. The annotations only say readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=true, and the description adds substantial context about response size, cost, and error handling. No contradiction with 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 dense but well-structured: it starts with the core purpose, then lists return fields, then provides size measurements, then cost, then envelope details. Every sentence adds value, though the size and cost details are somewhat lengthy. It is front-loaded with the most important information and uses formatting (⚠️, 💰) to draw attention to caveats. Slightly over-long but justified by the complexity.

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 output schema exists and the annotations provide some hints, the description is complete enough for an agent to call this tool correctly. It explains the response envelope, the synchronous behavior, the cost implications, and the result depth options. The only minor gap is that it doesn't explicitly list all parameters, but the schema already does that. For a complex tool with one body parameter, this is comprehensive.

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. The description does not explain individual parameters like language_code or location_code, but it does clarify the 'keyword' parameter by stating it returns ranked results for a keyword on YouTube. The description also mentions 'three result depths' which likely maps to a parameter not shown in the schema (maybe a 'depth' field), but the schema only shows one parameter 'body' with nested properties. Since the description adds context about the query and result structure but doesn't fully document each parameter, a 4 is appropriate rather than 5.

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 verb and resource: 'Returns the ranked results for a keyword on YouTube, synchronously.' It then lists the exact fields returned, which distinguishes it from sibling tools like get_youtube_search and other search tools. The title 'Live YouTube Organic Advanced' is also clarified by the description's mention of result depths and the 'advanced' default.

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 states when to use this tool versus alternatives: 'advanced is the default choice; take regular when only the ranked list matters and html only to check what the parser dropped.' It also mentions the cost advantage relative to other search data sources, which helps an agent decide when this tool is appropriate. This is clear usage guidance with explicit alternatives and conditions.

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