capcut_duck_music

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

With no annotations, the description carries the load and does well: it discloses that it writes keyframes on disk, that dry-run is the default, and clarifies the under/free semantics. It omits prerequisites such as CapCut being closed and permission requirements, which the schema only partially covers.

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?

A single dense, front-loaded sentence with a clarifying parenthetical; the core action leads and details follow. No wasted words, though the nested parenthetical is slightly crowded.

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 10-parameter, no-annotation, no-output-schema mutation tool, the description covers the core behavior and two key params but is silent on return/plan format and several parameters (ramp_s, merge_gap_s). Sufficient to start but not fully complete.

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 50%, so the description needs to compensate. It usefully explains 'under' (level during speech), 'free' (level between lines), and the default segment volume, but ramp_s, merge_gap_s, and track behavior are left to the schema, so it only partially closes the 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+resource (lower music under speech) and the exact mechanism (reads SRT cues, writes volume keyframes on the music track). This is clearly distinct from generic siblings like capcut_add_keyframes or capcut_add_audio, so an agent can select it without opening the schema.

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 scenario is implied by 'under speech' and 'reads SRT cues', so an agent can infer when it applies, but there is no explicit when-to-use/when-not guidance and no named alternative (e.g. vs. capcut_add_keyframes). Adequate but leaves routing to inference.

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