extract_video_clip

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

No annotations, so description carries full burden. It discloses buffer addition and clip saving location (~/clips/). Could mention file overwrite or permission requirements, but current details are sufficient for typical usage.

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?

Description is well-structured with a clear purpose, usage context, sample prompts, and parameter list. Front-loaded with key information. A bit lengthy but each sentence adds value.

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 5 parameters and no annotations, the description covers essential aspects: source, timestamps, buffer, output. Output schema exists, so return value details are not needed. Complete for its purpose.

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%, but description adds value by explaining each parameter in the Args section, including defaults for buffer_seconds and output_filename. This compensates for missing schema descriptions.

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?

Description clearly states the tool extracts a video clip by topic from a YouTube video or local file. Verb 'extract' and resource are specific, and it distinguishes from siblings like transcribe_video and convert_media.

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 'Used after transcribe_video' and describes the workflow where the LLM reads transcript to find timestamps. Also provides sample prompts, giving clear when-to-use guidance.

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