diatonic_chords

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

With no annotations, the description carries full burden. It discloses output format (roman numerals, degree names, harmonic functions) and special behavior for octave roots (MIDI numbers). However, it does not specify valid scale_type values, error handling, or limitations (e.g., only seven-note scales get full output).

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 front-loaded with the purpose and includes a clear example. The second paragraph adds useful context but is slightly verbose. Overall, it is efficient for the complexity of the tool.

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?

Given no output schema and moderate complexity, the description covers return values and a workflow. However, it lacks details on edge cases, valid inputs, and errors, which an agent would need for reliable invocation.

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 0%, so description must compensate. It only hints at 'root' and 'scale_type' via example, and 'sevenths' is mentioned but not explicitly described. No valid values or constraints for parameters are provided, leaving ambiguity for an AI agent.

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 lists chords built on each degree of a scale, with explicit example and mention of return values (roman numerals, degree names, harmonic functions). It distinguishes from sibling degrees_to_chords by describing a workflow.

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 a usage pattern: use this tool to get diatonic chords as raw material, then resolve with degrees_to_chords. It does not explicitly state when to avoid this tool, but the example and workflow guidance are sufficient for an AI agent to infer its primary use.

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