analyze_moment

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint values, so the safety profile is established. The description adds behavioral context by describing the composition of outputs (frames + transcript + OCR + unified timeline) and noting external dependencies like yt-dlp for certain platforms, which goes beyond the structured annotations.

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 front-loaded with a clear topic sentence, followed by a compact use-case list, a concrete example, and a concise support matrix. Each section earns its place and the structure makes it easy for an agent to scan and act on.

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?

For a tool with six parameters and no output schema, the description covers the core outputs, typical usage, parameter behavior, and supported input sources. It does not fully specify the exact response shape, but it provides enough context for an agent to select and invoke the tool appropriately.

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 baseline is 3. The description adds extra value by showing an example invocation mapping arguments to results, and by giving practical guidance on maxWidth for screen recordings with small text and context-cost tradeoffs. This meaningfully enriches the parameter understanding 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 it performs a 'deep-dive analysis' of a 'specific time range in a video' and names its combined outputs: burst frames, transcript filtering, OCR, and annotated timeline. This differentiates it from sibling tools like get_frame_at or get_transcript by emphasizing the integrated, segmented analysis. The example further concretizes the tool's purpose.

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?

It explicitly says 'Use this when you need to understand exactly what happens between two timestamps' and lists the visual and audio coverage of the tool. It does not name alternative tools to use instead, but the clear use case and supported platform list give strong contextual guidance.

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