run_surprise_detection

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

There are no annotations to signal safety or side effects. The description only mentions the return values, not whether the pipeline modifies files, requires a pre-loaded model (hinted by siblings load_model and get_model_status), or has performance implications. For a tool likely to depend on model state, this is a significant transparency gap.

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 that leads with the action, then states inputs and outputs. Every word is useful; there is no redundancy or extraneous information. It fits the ideal model of front-loaded, efficient prose.

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 pipeline tool with three parameters and no output schema, the description gives a good roll-up of what it does and returns. However, it omits the relationship with model loading (sibling load_model) and does not explain the processing steps or how threshold_multiplier affects results, which might be relevant for an agent deciding to use it. Overall, it is nearly complete but could add a prerequisite note.

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 input schema provides descriptions for all three parameters, matching the 100% schema coverage baseline. The description adds no parameter-specific detail beyond mentioning 'directory' and 'video file' as input types, which is already in the schema. It earns the baseline score of 3.

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 a specific action ('Run full surprise detection pipeline') with explicit input types (directory or video file) and output components (annotated timeline, frames exceeding threshold, summary stats). It distinguishes itself from siblings like analyze_screenshot and analyze_video by emphasizing the full pipeline on a batch of inputs.

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 usage for processing a directory of screenshots or a video file, which is clear context. However, it does not explicitly mention when to use this tool versus alternatives such as analyze_screenshot for single images or analyze_video for individual videos, nor does it state exclusions or prerequisites.

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