analyze_video

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: 'The model reads the video natively — no client-side frame extraction,' which sets expectations about processing. It also discloses the 25MB base64 guardrail for local files. While it doesn't cover error handling or response format, for a read-only analysis tool these are minor gaps.

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 efficiently written in four sentences, each serving a purpose: purpose, usage, processing behavior, and input format. It is front-loaded with the core function, and no words are wasted. This is a model of concise, informative documentation.

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 lack of output schema, the description is very close to fully complete. It explains what the tool does, when to use it, how it processes, and input constraints. The only small gap is not explicitly stating the return format, but that is implied by the question parameter and the analysis context. Overall, it is highly informative for a tool without annotations.

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 coverage is 100%, so the baseline is 3. The description adds meaningful info beyond the schema: it clarifies that video_url can be http/https or a local path, and that local files are sent as base64 data URL with a 25MB limit. This extra context helps the agent understand the parameter's constraints and behavior.

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 states the exact function: 'Watch and analyze a video using Qwen3.8-Max (native multimodal).' It clearly distinguishes this tool from siblings like analyze_image and analyze_audio, focusing specifically on video. The verb 'watch and analyze' plus resource 'video' makes the purpose unambiguous.

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 says 'Use this whenever you need to see a video you cannot view natively,' providing clear when-to-use guidance. It also gives practical input guidelines (public URL or local file path, base64 inline, 25MB guardrail). It does not explicitly mention alternatives or when not to use, but the context is sufficiently clear.

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