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module_check

Detects mismatched VAE or text encoders for the active architecture and lists installed files to fix the gap. Use after switching presets or when output looks wrong.

Instructions

Check the VAE and text encoders loaded for an architecture against what it actually needs, and list installed files that could fill any gap.

Defaults to the active preset. Worth calling after switching architecture or when output looks wrong for no obvious reason: Forge records the last selection made under a preset, so loading a checkpoint while another preset was active can leave the wrong modules attached. Where the reference does not state a VAE, it says so instead of guessing — a wrong VAE degrades output without raising an error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
presetNo
Behavior4/5

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

With no annotations, the description carries the burden of behavior. It discloses that it says when a VAE is not stated instead of guessing, and explains the preset behavior. It implies read-only operation by listing files and checking, which is transparent. No contradictions with annotations since none are provided.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet information-dense. It leads with the main purpose, then usage triggers, and finally a behavioral note. Each sentence contributes to understanding without fluff, and it is not overly long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers what, when, why, and what it returns (list of installed files). While no output schema is provided, listing files is enough for an agent to understand the output. The description also hints at edge cases (missing VAE) and the reasoning behind the need for this tool. It is complete for a simple one-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and there is only one parameter, preset. The description explains that it defaults to the active preset, which gives meaningful context for the parameter beyond the schema's default value. This compensates for the lack of schema documentation, though it does not specify format or types beyond the default.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the function: checking VAE and text encoders against architecture needs and listing installed files to fill gaps. It uses a specific verb (check) and resource (VAE and text encoders), and distinguishes itself from siblings like model_profile and module_download by focusing on module alignment, not profiling or downloading.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit scenarios for use: after switching architecture or when output looks wrong without obvious cause. It explains the underlying reason (preset selection recording) and gives a clear rationale for calling it. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of the highest bar.

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

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