find_dissonances

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

The description discloses the main behavior (finding dissonances and returning resolution advice) but lacks details on underlying theory, assumptions, or limitations. With no annotations, it is adequate but not comprehensive.

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 concise with a clear docstring structure (Args, Returns) and front-loaded purpose. Every sentence adds value without redundancy.

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 analysis tool with only two parameters and a clear output (list of dissonances), the description is fully complete. The output schema handles return details, and inputs are well documented.

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?

Despite 0% schema description coverage, the description compensates well by providing examples for 'pitches' and valid values for 'context', adding substantial meaning beyond the schema titles.

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 finds dissonant intervals in a collection of pitches, with an example. However, it does not explicitly distinguish from sibling tools like analyze_intervals or detect_parallel_motion.

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 provided on when to use this tool versus alternatives such as analyze_intervals or check_voice_leading. The context parameter hints at scenarios, but no explicit directives.

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