Normalize Loudness File

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

Annotations already indicate destructiveness and read-only behavior, and the description adds specific, valuable safety context: 'Never overwrites the input or an existing output file.' It also discloses the implementation approach (FFmpeg) and the post-measurement step, which go beyond the minimal annotation hints.

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 sentences with no filler. The key workflow and the most important safety constraint are front-loaded, and every phrase adds value.

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 file-creating tool with five parameters, the description, combined with full schema coverage and an output schema, provides enough context to call it correctly. It could mention the relationship to analyze_loudness, but the core workflow, safety guarantee, and tool boundaries are sufficiently clear.

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 description coverage is 100%, so the parameters are already well documented. The description adds no new per-parameter meaning beyond reinforcing that output_path must not pre-exist, which is already stated in the schema. 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 ('Create') and resource ('loudness-normalized media derivative'), and explains the two-step workflow with FFmpeg and EBU R128 remeasurement. This clearly distinguishes it from sibling tools like analyze_loudness that only measure without creating a new file.

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 implies its use case: when a new loudness-normalized derivative is needed. However, it does not explicitly state when to prefer this tool over alternatives such as analyze_loudness, nor does it provide any when-not-to-use guidance or exclusions.

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