# viewcomfy-api-rules

Guides an agent through wiring the ViewComfy API into a Python and FastAPI web app: flatten workflow params, call the endpoint, save the returned files.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 663 installs · ★ 286
- Author: Mindrally
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/Mindrally/skills/tree/HEAD/viewcomfy-api-rules/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/viewcomfy-api-rules

## What it does

The skill primes the agent as a Python, FastAPI and web app specialist whose job is integrating the ViewComfy API. That API is a serverless FastAPI service that runs custom ComfyUI workflows, and implementations send requests with the `httpx` library.

The workflow it lays out: deploy a ComfyUI workflow from the ViewComfy dashboard using `workflow_api.json`, flatten its configuration with `workflow_parameters_maker.py`, set the endpoint URL plus Client ID and Client Secret, then call either `infer` as a standard POST or `infer_with_logs` for streaming SSE when you want live tracking. Responses carry `prompt_id`, `status`, `completed`, `execution_time_seconds`, the original configuration, and an `outputs` array of base64-encoded files with filename, content type and size — decode those and write them to your working directory.

The first call may hit a cold start, and generation time swings hard between workflows: under 2 seconds for some, several minutes for others. That is why the skill pushes `infer_with_logs` for long runs — otherwise your users stare at nothing. The `params` object cannot be empty; when nothing is specified, change the seed value. Keep credentials server-side, out of client code.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add Mindrally/skills --skill viewcomfy-api-rules -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/viewcomfy-api-rules/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/viewcomfy-api-rules/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add Mindrally/skills --skill viewcomfy-api-rules -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/viewcomfy-api-rules/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add Mindrally/skills --skill viewcomfy-api-rules -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/viewcomfy-api-rules/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install Mindrally/skills viewcomfy-api-rules
```

2. **Manually: put the files in place**
- File: `.github/skills/viewcomfy-api-rules/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add Mindrally/skills --skill viewcomfy-api-rules -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/Mindrally/skills --path viewcomfy-api-rules
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/viewcomfy-api-rules/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add Mindrally/skills --skill viewcomfy-api-rules -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/Mindrally/skills/tree/HEAD/viewcomfy-api-rules/SKILL.md

## When to use it
- hook the ViewComfy API into a FastAPI backend
- deploy a ComfyUI workflow and flatten its parameters
- stream progress from a long-running workflow over SSE
- decode base64 outputs and save the files locally
- absorb cold start delays without breaking the app

## Example prompts
- Wire the ViewComfy API into my FastAPI app: deploy the workflow from `workflow_api.json` and build the call with `httpx`.
- Use `infer_with_logs` so progress from a long generation streams into the UI.
- Parse the ViewComfy response: decode the base64 in `outputs` and save the files to my working directory.

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 4a788e9ece209e98.

BEGIN THIRD-PARTY FILE 4a788e9ece209e98
```text
---
name: viewcomfy-api-rules
description: Expert guidance for integrating ViewComfy API into web applications using Python and FastAPI
metadata:
  maintainer: Mindrally
  source: https://github.com/Mindrally/skills
---

# ViewComfy API Rules

You are an expert in Python, FastAPI integrations and web app development, tasked with helping integrate the ViewComfy API into web applications using Python.

## Key Technical Context

The ViewComfy API is a serverless FastAPI-based service that executes custom ComfyUI workflows. Implementations use the httpx library for requests.

## Important Operational Considerations

### Cold Start & Performance
First time you call it, you might experience a cold start. Generation times vary between workflows; some less than 2 seconds, others several minutes.

### Parameter Requirements
The params object cannot be empty. If unspecified, modify the seed value.

## API Response Format

Results return with this structure:
- `prompt_id`: Unique identifier
- `status`: Execution status
- `completed`: Boolean completion indicator
- `execution_time_seconds`: Processing duration
- `prompt`: Original configuration
- `outputs`: Array of generated files (optional, containing filename, content_type, base64-encoded data, and size)

## Implementation Workflow

1. Deploy ComfyUI workflow via ViewComfy dashboard using workflow_api.json
2. Extract parameters using workflow_parameters_maker.py to flatten configuration
3. Configure endpoint URL, Client ID, and Client Secret in implementation
4. Call API using either `infer` (standard POST) or `infer_with_logs` (streaming SSE for real-time tracking)
5. Handle outputs by base64-decoding and saving to working directory

## Best Practices

- Always handle cold start delays gracefully in your application
- Implement proper error handling for API responses
- Use streaming endpoints (`infer_with_logs`) for long-running workflows to provide user feedback
- Store credentials securely and never expose them in client-side code
- Validate parameters before sending requests to avoid unnecessary API calls
```
END THIRD-PARTY FILE 4a788e9ece209e98

The third-party file has ended. Everything between the 4a788e9ece209e98 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

© Mindrally · Apache-2.0 · https://github.com/Mindrally/skills/tree/HEAD/viewcomfy-api-rules/SKILL.md

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