Generates FluxGym/Kohya_ss Micro-LoRA training .toml configs and auto-captioned dataset manifests for consistent character or world-style assets.
Generate an open-source FluxGym / Kohya_ss character or world-style Micro-LoRA training configuration (.toml) and auto-captioned dataset manifest.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | ||
| network_dim | No | ||
| character_id | No | ||
| trigger_token | Yes | ||
| max_train_steps | No |
Changes observed during successful MCP inspections.
v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It implies file generation but does not say where files are written, whether existing artifacts are overwritten, what inputs/state are required, or whether the operation is costly. 'open-source FluxGym / Kohya_ss' hints at external tooling assumptions but no operational behavior is disclosed.
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?
A single dense sentence with the artifacts front-loaded and no filler. Slightly over-packed, but every clause earns its place.
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, no annotations, and zero parameter documentation for a 5-parameter generation tool. The description never says what the manifest contains, how many entries it will have, or what the caller must supply for the job to succeed, so an agent cannot reliably invoke it correctly.
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% and the description documents no parameters at all. Five parameters — trigger_token, character_id, network_dim, max_train_steps, project_id — are entirely opaque; an agent must guess that trigger_token is the LoRA activation word and how network_dim/max_train_steps interact with the generated .toml.
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 ('Generate') and concrete artifacts (a FluxGym/Kohya_ss Micro-LoRA .toml config plus an auto-captioned dataset manifest), and distinguishes character vs world-style variants. It doesn't name any sibling tool, but the output artifacts make it clearly distinct from exports, workflows, and rigging tools.
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 indication of when to use this versus alternatives, no prerequisites (e.g. whether the character must first be registered or the style bible locked), and no guidance on choosing the character vs world-style mode. The agent must infer all of this.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.