prepare_video_context

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

With no annotations, the description must fully disclose behavior. It states it analyzes and saves, but does not mention side effects (e.g., cache creation, disk usage), required permissions, or whether it is a read-only or destructive operation. This is insufficient for an agent to anticipate consequences.

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 sentence, which is concise but lacks structure. It does not front-load critical information or use scannable elements. While not verbose, it omits details that could be organized into a clear, brief format.

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 has 5 parameters, no annotations, and many siblings, a one-sentence description is severely incomplete. It does not explain input parameter roles, output structure (despite output schema existing), or operational constraints. The agent cannot reliably select or invoke this tool correctly.

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%, yet the description provides no explanations for any of the five parameters (url, model, detail, chunk_seconds, force_refresh). The agent must guess their semantics from names alone. This fails to add value beyond the 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 clearly states the tool's purpose: analyzing an entire video and saving a structured context. It differentiates from siblings like analyze_video_segment (segment-level) and watch_and_analyze (real-time) by specifying 'whole video once' and 'save'. This aligns with the verb+resource expectation.

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 the tool is for one-time full analysis before querying contexts (e.g., ask_video_context), but it does not explicitly state when to use it over alternatives like analyze_video or when not to use it. The context is clear but lacks explicit exclusions or alternative names.

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