Detect scene changes

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

With no annotations, the description carries the transparency burden. It discloses that the tool returns a list of cut times and is a detection operation (non-destructive), but does not elaborate on edge cases (e.g., no cuts found) or output format specifics. This is adequate but not rich.

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, front-loaded with the core action, followed by the output's use case. Every word earns its place, with no redundant information.

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?

There is no output schema, so the description must explain return values, which it does ('Returns a list of cut times'). It also connects to sibling tools for a complete workflow. Minor gaps include lack of timestamp format details or handling of edge cases, but overall it is complete for a simple detection tool.

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 100% and both parameters have descriptive text in the schema (e.g., threshold sensitivity range and default, input_path purpose). The description itself does not add parameter-level detail beyond the schema, so baseline 3 is appropriate.

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 uses a specific verb ('Find') and identifies the resource ('timestamps where the picture changes abruptly'), clearly distinguishing it from siblings like detect_silence and editing tools. It also explains the output's purpose (cut times for trimming/concat), making the tool's function 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 states that the returned cut times can be fed into trim_video/concat_videos, giving clear downstream usage context. It does not explicitly mention when not to use it or alternatives, but the intended workflow is clear enough for an AI agent to select it appropriately.

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