watch_and_analyze

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

No annotations provided, but description explains download, AI analysis, JSON return, async behavior for TikTok/Instagram, and clarifies non-execution. Could elaborate on data retention or rate limits, but covers essential behavioral traits.

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?

Concise yet comprehensive: first sentence states purpose, second paragraph explains behavior with platform differences, third clarifies non-execution. No redundant information, front-loaded.

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?

Fully covers tool complexity: async polling, platform-specific behavior, reference to sibling tool for execution, and non-execution guarantee. Output schema exists to detail return format.

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?

Input schema covers 100% of parameters with descriptions. Description does not add meaningful extra information beyond what schema provides (language hint defaults, model selection). Baseline score retained.

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?

Describes specific verb 'Watch' and 'extract' with resource 'video tutorial' and what is extracted (commands, code, steps). Distinguishes from siblings like 'analyze_video' by focusing on tutorial steps extraction.

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?

Explicitly states when to use (for analysis only) and when not (use execute_tutorial_steps for execution). Also differentiates behavior across platforms (YouTube vs TikTok/Instagram) and directs to check_analysis_job for polling.

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