popcorn_analyze

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the primary actions (extract keyframes and transcripts) but does not disclose side effects, resource usage, output location, potential failures, or how the analysis bundle is returned or stored. The description is too thin for a tool with 16 parameters and no annotation context, leaving significant behavioral unknowns.

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 two sentences long, front-loads the primary purpose, and includes a useful recommendation without any fluff. Every sentence contributes meaning, making it appropriately concise and well-structured.

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's complexity (16 params, no output schema, no annotations), the description is minimal but not entirely inadequate. It states the core outputs and suggests a workflow with popcorn_suggest, but it does not explain what the analysis bundle contains or how to read results (e.g., via popcorn_read). The schema covers parameters richly, but the overall context for using this tool in the sibling workflow is incomplete, earning a middle score.

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?

The schema already covers all 16 parameters with 100% description coverage, so the baseline is 3. The description adds value by indicating that 'videoType and objective to use smart presets'—a cross-parameter relationship not explicit in the individual schema descriptions. This enhances the agent's understanding of how to combine parameters for optimal use.

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 function: 'Analyze a video file.' and specifies its key outputs: 'Extracts keyframes and transcripts.' This is a specific verb+resource combination that differentiates it from the sibling tool popcorn_suggest, which recommends settings rather than performing analysis. The purpose is immediately clear and 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 provides explicit usage guidance: 'RECOMMENDED: First use popcorn_suggest to get optimal settings, or specify videoType and objective to use smart presets.' This tells the agent when to use this tool relative to popcorn_suggest and offers an alternative path using parameters. It lacks an explicit 'when not to use' exclusion, which prevents a perfect score, but the guidance is clear and actionable.

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