set_clip_quantization

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

The description explains the integer-to-quantization mapping, which is the key behavioral aspect. However, it does not disclose whether the change is global and affects all clips, or if there are any side effects. No annotations are provided, so the description carries the burden but is only partially transparent.

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 extremely concise: one sentence for purpose followed by a clear mapping list. No superfluous words, well-structured for quick comprehension.

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 simple setter with an output schema, the description covers the purpose and parameter meaning. It could explicitly state that the setting is global, but overall it is complete enough for agent decision-making.

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%, so the description fully explains the parameter. It maps each integer value (0-8) to its quantization length (None, 8 bars, etc.), adding significant meaning beyond the schema's bare integer type.

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 explicitly states 'Set global clip launch quantization' which is a specific verb-resource pair. It distinguishes itself from siblings like 'set_midi_quantization' by specifying 'clip launch'. The mapping of values is clearly provided.

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?

No guidance is given on when to use this tool versus alternatives such as 'quantize_clip' or other quantization tools. No context about prerequisites, typical use cases, or when not to use it.

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