analyze_video_content

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the external API vendor and the analysis purpose, which is useful. However, it does not disclose that this likely triggers an external network call, may require cloud credentials, may internally extract keyframes, or has cost implications — all relevant for an agent deciding to invoke it.

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 a single clear sentence with no wasted words, and it is front-loaded with the core action and resource. It loses one point because it could easily include a brief note about the external API and output without becoming verbose.

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?

This is a minimal viable description: purpose is clear, params are fully documented, but there is no output schema and no annotations. The agent is left without guidance on what the return value looks like, how errors surface (e.g., invalid video path, API failure), or that running the tool consumes cloud resources. For an external-API-backed tool, this is a notable gap.

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 100%, so the schema fully documents all seven parameters. The description adds the vendor/API context but no parameter-specific semantics beyond what the schema already provides. Baseline 3 is appropriate because the schema does the heavy lifting.

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 names a specific verb and resource ('analyze video content') and identifies the concrete implementation (Tencent Hunyuan multimodal API). This clearly distinguishes it from frame-extraction and video-info tools. The only weakness is that it does not explicitly differentiate from analyze_image_batch beyond the medium.

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 implies this tool should be used when a video needs content analysis via the Tencent Hunyuan multimodal API. However, it gives no explicit when-to-use versus alternatives like analyze_image_batch or extract_video_frames, nor any conditions or exclusions. The routing context is weakly implied rather than stated.

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