extract_key_points

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

With no annotations, the description carries the full burden but only states 'Returns: Formatted key points'. It does not disclose any behavioral details such as whether captions are required, error behavior, or limitations on num_points, so the agent lacks transparency about the tool's behavior.

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 concise and well-structured with Args and Returns sections. It is front-loaded with the purpose, but the structure could be slightly improved by integrating parameter descriptions into the schema, though overall it is efficient.

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 simplicity and the presence of an output schema for return values, the description is mostly complete. However, it lacks usage context relative to sibling tools and fails to mention any prerequisites or edge cases, which is a gap for an AI agent deciding when to invoke this tool.

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?

Although schema description coverage is 0%, the description compensates by clearly explaining each parameter: video_url as 'YouTube URL or video ID', num_points as 'Number of key points to extract' with default, and language as 'Language code' with default. This adds meaningful semantic context beyond the raw schema.

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 uses a specific verb 'Extract' with a clear resource 'key points from a YouTube video', and this distinguishes it from siblings like get_transcript, summarize_video, and get_video_metadata, which serve different purposes.

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?

No guidance is provided on when to use this tool versus the sibling tools. The description only lists arguments and return value without specifying the ideal use case or exclusions, leaving the agent to infer usage.

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