Arrange a 4-piece band from a natural-language prompt. Returns conductor tempo/groove, 4 lanes of note events, lead sheet, and base64 MIDI. Audio render (Csound → WAV) stays on local thiri-conductor-mcp / POST /v2/render.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | ||
| durationSec | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it returns specific artifacts (tempo/groove, note lanes, lead sheet, base64 MIDI) and notes that audio rendering is deferred to an external endpoint, preventing misconceptions.
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?
Three purposeful sentences: purpose, output contents, and rendering behavior. Each sentence carries distinct information without redundancy or fluff, making it front-loaded and efficient.
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?
No output schema exists, but the description lists key return values adequately. However, it omits parameter details (durationSec) and any prompt constraints, leaving users guessing on important inputs for a complex generation tool.
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 coverage is 0%, so the description must document parameters. It only implicitly covers 'prompt' via 'natural-language prompt'; 'durationSec' is entirely undocumented. This is a significant gap for schema-less parameters.
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 arranges a 4-piece band from a natural-language prompt, using the specific verb 'arrange' and resource 'band.' This distinguishes it conceptually from sibling tools focused on chord analysis, voicing, reharmonization, or chord resolution.
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 clearly signals use cases: when a full band arrangement from a natural-language prompt is needed. It does not explicitly name alternatives or exclusions, but the context is unambiguous compared to more granular sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
analyze_chord, resolve_chord, and generate_voicing all operate on chord content and can easily be confused without reading the full descriptions. conduct_band is a clear outlier, while only reharmonize has a distinctly separate purpose.
Most tools follow a clean verb_noun snake_case pattern: analyze_chord, resolve_chord, generate_voicing, and conduct_band. reharmonize breaks the pattern by being a bare verb, but the naming style is otherwise predictable.
Five tools is a reasonable size for a focused server and avoids tool overload. However, conduct_band feels like it belongs in a separate arranging/conductor server rather than a chord intelligence server, which slightly weakens the set's focus.
The core chord-intelligence tasks are covered: analysis, resolution, voicing, and reharmonization. Missing obvious operations like chord inversion, transposition, or progression generation create noticeable gaps, and audio rendering is explicitly delegated elsewhere.