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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the output contents (integrated LUFS target, true peak limit, short-term LUFS), and clarifies scope ('not limited to the OnChain Music catalog'). This goes beyond a simple 'get' and provides a good transparency baseline, though it doesn't describe edge cases or format details.

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 long, front-loaded with the core purpose, and each sentence earns its place (purpose, then use cases/scope). No filler or 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?

For a simple tool with one optional parameter, no output schema, and good annotations-like context in the description, the description fully covers what an agent needs to know: what the tool returns, why to use it, and that it applies broadly. The context is 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?

The input schema already documents the single platform parameter with examples and a description, achieving 100% coverage. The tool description adds no additional meaning beyond what the schema provides, so the baseline score of 3 applies.

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 clearly identifies the tool's purpose: 'Returns the official loudness normalization standards for major music and video platforms.' It names a specific resource (loudness standards) and a specific action (returns), and distinguishes itself from sibling tools like get_genre_conventions and search_catalog, which serve different functions.

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 provides concrete use cases: 'Useful for mastering decisions, mix prep, and ensuring tracks meet platform requirements before distribution or licensing.' It doesn't explicitly state when not to use it or mention alternatives, but the context is clear enough that an agent can infer appropriate usage. This is close to explicit guidance, hence a 4.

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