segment_episodes

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

With no annotations, the description carries the full burden. It explains the algorithmic basis but says nothing about whether it mutates the dataset or returns segments, what the output shape is, or what happens to unsegmented frames — significant gaps for a processing tool.

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?

Two tight sentences with the action front-loaded and no filler. Efficient, though it is concise at the cost of necessary detail.

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?

A four-parameter processing tool with no annotations, no output schema, and zero parameter descriptions needs considerably more explanation than two sentences. The agent lacks enough to invoke it confidently.

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 coverage is 0% and four parameters exist. The description only loosely gestures at 'feature' via 'feature-speed percentiles'; path, episode, and min_frames (default 5) are left entirely unexplained, so it does not compensate for the schema gap.

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?

States a specific verb (split) and resource (episodes) with the segmentation criterion (moving/idle via feature-speed percentiles). Sibling tools are dataset-level operations, so there is little confusion risk, but the description does not explicitly differentiate itself from them.

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?

'Useful for phase labelling and for trimming dead time' implies downstream use cases but gives no explicit when-to-use/when-not guidance or alternatives. An agent must infer the trigger conditions.

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