Queue a Shadow Music Generator job to validate a prompt with dry-run or run local AI music generation. Dry-run jobs validate the request without running a model.
Queue a Shadow Music Generator job. Dry-run validates the request and never runs a model.
| Name | Required | Description | Default |
|---|---|---|---|
| run | No | Run immediately. Dry-run jobs always run. | |
| mode | No | dry-run | |
| model | No | ||
| lyrics | No | ||
| prompt | Yes | ||
| job_dir | No | ||
| output_dir | No | ||
| source_audio | No |
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that dry-run validates without running a model, but says nothing about queueing semantics, async behavior, permissions, or how this differs behaviorally from run_job. Adds real context but leaves significant gaps for a job-submission mutation.
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?
Two sentences, front-loaded with the action, no filler. Efficient even if under-informative.
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 an 8-parameter job-submission tool with no annotations and no output schema, the description is far too thin: it omits return/queue semantics, parameter meanings, and its relationship to the run_job and job_status siblings.
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 only 13% across 8 parameters; only 'run' and 'mode' have any hint of meaning. The description mentions dry-run but does not explain model, lyrics, prompt, job_dir, output_dir, or source_audio, nor the relationship between the 'run' flag and 'mode'.
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?
States a specific verb (queue) and resource (Shadow Music Generator job), clearly distinguishing it from siblings run_job and job_status. Slightly weakened by the unfamiliar product name 'Shadow Music Generator' which the description does not explain.
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 on when to use this versus run_job, yet the overlap is obvious since both submit/run jobs and the 'run' flag exists here. The dry-run behavior is mentioned but not framed as a usage decision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.