effect_clip_fix

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

With no annotations, the description must carry behavioral transparency itself. It discloses the operation and reconstruction approach, but does not state that the effect modifies the selected audio in place, whether it is destructive, or how it handles borderline clipping. The word 'Attempt' does signal heuristic behavior, but key application context is missing.

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 tightly scoped parts: a one-sentence purpose followed by an Args block. No filler or repeated schema information, and the main behavior is front-loaded.

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 one-parameter effect with no output schema, the description is mostly sufficient to call it; threshold semantics are fully specified. The main missing piece is the application context (selected audio) and a hint to detect clipping first, which would help an autonomous agent sequence it.

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 description adds real meaning to threshold: it defines it as a percentage of max amplitude, gives a 0-100 range, and restates the default. The schema only provides a type and default, so this is a substantial addition.

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 ('repair'), names the target resource ('clipped audio'), and explains the method ('reconstructing peaks'). This clearly differentiates it from generic siblings like effect_repair.

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 about when to apply this tool versus alternatives such as effect_repair or analyze_find_clipping. The context of an active selection or prerequisite is not mentioned, so an agent must infer usage from the name.

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