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health_check

Run pre-flight diagnostics on a connected ComfyUI instance to check version, GPU and memory status, queue depth, model populations, and recent errors before dispatching a batch or troubleshooting failures.

Instructions

Pre-flight diagnostic for the connected ComfyUI: one call that aggregates the signals an agent should check before dispatching a batch. Reports ComfyUI version/Python/PyTorch, GPU name + VRAM free/total, system RAM free, queue depth (running + pending), per-category /models populations (catches empty dropdowns from a misconfigured extra_model_paths.yaml), and recent errors from /internal/logs. Read-only — no mutation. Use this when a job fails for an unexpected reason, before a long batch run, or to confirm a remote ComfyUI is healthy. Originally contributed by github.com/joaolvivas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_categoriesNoOverride the model categories to poll (defaults to checkpoints, diffusion_models, loras, vae, text_encoders, controlnet).
recent_errorsNoHow many recent error/traceback lines to include from /internal/logs (default 20, max 200).
Behavior4/5

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

No annotations provided, so description carries full burden. It details what data is reported (version, GPU, RAM, queue, models, errors) and explicitly states 'Read-only — no mutation.'

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?

Six concise sentences, front-loaded with purpose, followed by details and usage. No wasted words.

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

Completeness5/5

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

Despite no output schema, the description lists all report components comprehensively. No missing information for an agent to understand the tool's output.

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

Parameters3/5

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

Schema coverage is 100% with descriptions for both parameters. The description reiterates defaults and max values but adds little beyond schema.

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?

Description clearly states the tool is a 'Pre-flight diagnostic' for ComfyUI, listing specific signals aggregated. It distinguishes itself as the only health/diagnostic tool among siblings.

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?

Explicit usage scenarios: 'when a job fails for an unexpected reason, before a long batch run, or to confirm a remote ComfyUI is healthy.' Read-only nature is stated but no alternatives named.

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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