random_notes

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

The description details that the selection is a 'pure dice roll', octaves are preserved, and the operation is reproducible via a seed which is always returned. This goes beyond mere operation to provide behavioral insight, compensating for the absence of annotations.

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 short (three sentences) and front-loads the main purpose. It uses clear language but could be slightly more structured with explicit parameter descriptions.

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?

With no output schema and no annotations, the description should explain the return value. It only mentions that the seed is returned, but not the format of the random notes themselves. This omission leaves the agent uncertain about the output structure, reducing completeness.

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 explains 'count' and 'seed' parameters (count controls number of picks, seed for reproducibility). However, 'notes' and 'allow_repeats' are not described; the schema has 0% coverage, so the description should have covered all parameters. It adds partial value but is incomplete.

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 states the tool picks uniformly random notes from a pool, with an example referencing get_scale/get_chord. This distinguishes it from sibling tools like get_chord or get_scale, which produce deterministic outputs.

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 indicates the typical source of the pool (get_scale/get_chord) and that this is a random selection. It provides context for when to use this tool but does not explicitly mention when not to use it or suggest alternatives.

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