runcomfy-cli

作成者: doany-ai

We need to translate the given English text into Japanese. The text describes a CLI tool called runcomfy-cli. The instruction says to preserve the name "runcomfy-cli" but only if it appears in the source text. The source text mentions "runcomfy" and "runcomfy CLI" but not "runcomfy-cli" exactly. However, the directory item type is "agent skill" and the name to preserve is "runcomfy-cli". The instruction says "Do not include the name unless it appears in the source text." The source text has "runcomfy" and "runcomfy CLI", not "runcomfy-cli". So we should not add "runcomfy-cli" if it's not there. But the instruction says "Name to preserve: runcomfy-cli" and "Translate only the text inside <text>. Do not include the name unless it appears in the source text." So we only translate the text inside <text>. The text inside <text> includes "runcomfy" and

npx skills add https://github.com/doany-ai/skills --skill runcomfy-cli

RunComfy CLI

One binary, one auth, every RunComfy model. Install once, sign in once, then call any text-to-image, video, edit, lip-sync, face-swap, or LoRA-training endpoint with runcomfy run <model_id> --input '{...}'. This skill is the foundation every other runcomfy-* skill builds on.

runcomfy.com · CLI docs · All models

Install this skill

npx skills add agentspace-so/runcomfy-agent-skills --skill runcomfy-cli -g

Install the CLI

Pick one:

# Global install via npm (recommended for repeat use)
npm i -g @runcomfy/cli

# Zero-install one-shot (no Node global state)
npx -y @runcomfy/cli --version

A standalone curl-pipe installer also exists for environments without Node — see docs.runcomfy.com/cli/install. Inspect any install script before piping it into a shell. This skill only invokes the CLI via Bash(runcomfy *) after you have installed it through one of the verified package managers above.

Confirm:

runcomfy --version

Full options on the Install page.

Sign in

Interactive (opens browser):

runcomfy login
# Code shown in terminal — paste into the browser page, click Authorize
# Token saved to ~/.config/runcomfy/token.json with mode 0600

CI / containers (no browser):

export RUNCOMFY_TOKEN=<token-from-runcomfy.com/profile>

Verify:

runcomfy whoami
# 📛 you@example.com
#    token type: cli
#    user id: ...

Full flow + token rotation: Authentication.

Run a model

The general shape:

runcomfy run <vendor>/<model>/<endpoint> \
  --input '<JSON body>' \
  --output-dir <path>

Example — generate an image with GPT Image 2:

runcomfy run openai/gpt-image-2/text-to-image \
  --input '{"prompt": "a small purple cat at sunset, photorealistic"}'

You will see:

⏳ Submitting request to openai/gpt-image-2/text-to-image
   request_id: 8a3f...
⏳ Polling status (every 2s)...
   in_queue
   in_progress
   completed
✅ completed
{
  "images": [
    "https://playgrounds-storage-public.runcomfy.net/.../result.png"
  ]
}
📥 Downloading 1 file(s) to .
   ./result.png

By default the result is downloaded to the current directory. Override with --output-dir ./out, skip downloading with --no-download.

Quickstart: docs.runcomfy.com/cli/quickstart.

Discover model schemas

Every model has an API tab on its detail page with the exact input schema. Browse the catalog:

open https://www.runcomfy.com/models

Or search by collection / capability:

URLWhat
/modelsAll featured models
/models/allThe full catalog
/models/collections/recently-addedFresh additions
/models/collections/nano-banana · /seedream · /flux-kontext · /kling · /seedance · /veo-3 · /wan-models · /hailuo · /qwen-imageCurated brand collections
/models/feature/lip-syncLip-sync capability
/models/feature/character-swapCharacter / face swap
/models/feature/upscale-videoVideo upscalers

Commands

runcomfy run <model_id>

Synchronous run — submit, poll, download.

FlagWhat
--input '<JSON>'Inline JSON body. Strings can contain newlines; quote-escape as needed
--input-file <path>Read body from a file (JSON or YAML by extension)
--output-dir <path>Where to download result files (default: cwd)
--no-downloadSkip the download step; only print the result JSON
--no-waitSubmit and return request_id immediately; don't poll
--timeout <seconds>Cap the polling wait. Default: model-dependent
--output jsonPrint machine-readable JSON for piping (default human-readable)
--quietSuppress progress, keep only the final result line

runcomfy login / runcomfy whoami / runcomfy logout

login runs the device-code flow; whoami prints the active identity; logout removes the local token file. Set RUNCOMFY_TOKEN env var to override the file entirely.

runcomfy status <request_id>

Check status of a --no-wait job:

RID=$(runcomfy --output json run google/nano-banana-2/text-to-image \
  --input '{"prompt": "..."}' --no-wait | jq -r .request_id)

runcomfy status "$RID"

Full command reference: docs.runcomfy.com/cli/commands.

Scripting patterns

Pipe-friendly JSON

runcomfy --output json run openai/gpt-image-2/text-to-image \
  --input '{"prompt": "X"}' \
  --no-download \
| jq -r '.images[0]'

Batch from a file of prompts

while IFS= read -r prompt; do
  runcomfy run blackforestlabs/flux-2-klein/9b/text-to-image \
    --input "$(jq -nc --arg p "$prompt" '{prompt:$p, steps:8}')" \
    --output-dir "./out/$(date +%s%N)"
done < prompts.txt

Submit now, poll later

# Submit one or many jobs without blocking
RID=$(runcomfy --output json run bytedance/seedance-v2/pro \
  --input '{"prompt": "..."}' --no-wait | jq -r .request_id)

# Later — possibly from a different shell:
runcomfy status "$RID"

Retry on transient failure

The CLI returns exit code 75 on retryable errors (timeout, 429). Wrap with a shell retry loop:

for i in 1 2 3; do
  runcomfy run <model_id> --input '{...}' && break
  rc=$?
  [ $rc -eq 75 ] && sleep $((2**i)) && continue
  exit $rc
done

Exit codes

codemeaningretry?
0success
64bad CLI argsno
65bad input JSON / schema mismatchno
69upstream 5xxyes (after backoff)
75retryable: timeout / 429yes
77not signed in or token rejectedno — re-auth
130interrupted (Ctrl-C); remote request is cancelled before exit

Full reference: docs.runcomfy.com/cli/troubleshooting.

How it works

The CLI does three things for each run call:

  1. Submit — POSTs the JSON body to model-api.runcomfy.net with your bearer token.
  2. Poll — GETs the request every ~2s until status is completed, failed, or canceled.
  3. Download — for each output URL under *.runcomfy.net / *.runcomfy.com, fetch into --output-dir.

Ctrl-C sends DELETE to the request endpoint to cancel the remote job before exit, so you don't get billed for work you abandoned.

Security & Privacy

  • Install via verified package manager only. This skill recommends npm i -g @runcomfy/cli or npx -y @runcomfy/cli. A standalone curl-pipe installer exists in the official docs but agents must not pipe an arbitrary remote script into a shell on the user's behalf — if the user wants the curl path, they should review the script themselves first.
  • Token storage: runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner-only read/write). Set RUNCOMFY_TOKEN env var to bypass the file entirely in CI / containers. Never log the token, never echo it into prompts, never check it into a repo.
  • Input boundary (shell injection): prompts are passed as a JSON string via --input. The CLI does not shell-expand prompt content; it transmits the JSON body directly to the Model API over HTTPS. There is no shell-injection surface from prompt content, even when the prompt contains backticks, quotes, or $(...) patterns.
  • Indirect prompt injection (third-party content): image / audio / video URLs and enable_web_search outputs are untrusted. They are fetched by the RunComfy model server and can influence generation through embedded instructions inside the asset (e.g. text painted into an image, hidden instructions in EXIF, web-search results steering style). Mitigations the agent should apply:
    • Only ingest URLs the user explicitly provided for this task. Don't auto-resolve URLs the user pasted in unrelated context.
    • When generation behavior diverges from the prompt, suspect the reference asset, not the prompt.
    • For enable_web_search, default to false; set true only when the user names a real-world entity that requires grounding.
  • Outbound endpoints (allowlist): only model-api.runcomfy.net (request submission) and *.runcomfy.net / *.runcomfy.com (download whitelist for generated outputs). No telemetry. No callbacks to third parties.
  • Generated-file size cap: the CLI aborts any single download > 2 GiB to prevent disk-fill from a runaway model output.
  • Scope of this skill's bash usage: declared allowed-tools: Bash(runcomfy *). The skill never instructs the agent to run anything other than runcomfy <subcommand>npm, curl, export RUNCOMFY_TOKEN=... lines in this document are install / one-time setup steps for the operator, not commands the skill itself executes on each call.

See also

Sibling intent-routed skills that all dispatch through this CLI:

doany-aiのその他のスキル

image-edit
doany-ai
RunComfy上で画像を編集します。このスキルは、ユーザーの意図に合った編集モデルをRunComfyカタログから選択するスマートルーターです。Nano Banana Edit(最大20枚のバッチ処理、デフォルトで同一性保持)、OpenAI GPT Image 2 Edit(多言語対応の画像内テキスト書き換え、マルチリファレンス合成、レイアウト精度)、Flux Kontext Pro(単一リファレンスの高忠実度ローカル編集)、またはZ-Image Turbo Inpaint(マスク駆動の精密領域編集)を選択します。各モデルの文書化されたプロンプトパターンをバンドルしているため、スキルは…
creativeimagemedia
seedance-v2
doany-ai
ByteDance Seedance 2.0 Proを使用して、RunComfy上で映画的なショートフォーム動画を生成します。Seedance 2.
videocreativemedia
kling-3-0
doany-ai
RunComfy上でのKling 3.0動画生成。Kling 3.0(Kling V3.0とも呼ばれる)は、快手科技の第3世代マルチショット動画モデルで、ネイティブ同期オーディオとショット間で一貫したキャラクター同一性を備えています。このスキルは、3つのレンダリングティア(Standard、Pro、4K)と2つのモード(テキストから動画、画像から動画)にわたる、全6つのKling 3.0エンドポイントをカバーします。ローカルのRunComfy CLIを通じて、runcomfy run kling/kling-3.0/ / を呼び出します。"kling"、"kling 3.0"、"kling v3"、"kling pro"などでトリガーされます。
videocreativemedia
face-swap
doany-ai
Swap a face / character into video or images on RunComfy via the `runcomfy` CLI. Routes across community Wan 2-2 Animate (audio-driven character animation + identity swap), GPT Image 2 Edit (single-shot precise face swap on still images via reference composition), Nano Banana Edit (batch identity-preserving swap), Flux Kontext (single-ref high-fidelity local face edit), and Kling 2-6 Motion Control Pro (transfer motion from one performance onto a target character). Picks the right model for...
creativevideoimage
video-outpainting
doany-ai
Video outpainting on RunComfy via the `runcomfy` CLI — extend the spatial canvas of a video, change aspect ratio (9:16 vertical to 16:9 horizontal or vice versa), add environment beyond the original frame while preserving the central action. Routes prompt-shaped spatial extension through Wan 2-7 edit-video and points the agent at dedicated ComfyUI outpaint workflows when seam quality matters for hero delivery. Triggers on "video outpaint", "video outpainting", "extend video canvas", "expand...
videocreativemedia
ai-avatar-video
doany-ai
Create AI avatar, talking-head, and lip-sync videos on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar), Wan-AI Wan 2-7 (audio-driven mouth sync via `audio_url` on a portrait), HappyHorse 1.0 (Arena #1 t2v / i2v with in-pass audio), and Seedance v2 Pro (multi-modal cinematic with reference audio + reference subject). Picks the right model for the user's actual intent — UGC voiceover, virtual presenter, dubbed product demo, lip-synced...
videocreativemedia
flux-kontext
doany-ai
RunComfy上でFlux 1 Kontext Pro(Black Forest Labsの高精度ローカル画像編集モデル)を使用して画像を編集します。このスキルには、モデルのドキュメント化されたプロンプトパターンがバンドルされており、同じモデルに対して単純なプロンプトを使用するよりもシャープな出力が得られます。Flux Kontextの強み(単一参照による高精度ローカル編集、強力なプロンプト制御、一貫した高忠実度出力)、スキーマ(単一画像+プロンプト)、およびNano Banana Edit / GPT Image 2 edit / Flux 2 Kleinにルーティングするタイミングを文書化しています。呼び出し...
creativeimagedocument
relight
doany-ai
Relight a still image — change the lighting setup, color temperature, direction, or mood — on RunComfy via the `runcomfy` CLI. Routes to Qwen Edit 2509's dedicated `relight` LoRA endpoint for purpose-built relighting, with fallback to identity-preserving edit endpoints (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when prose lighting language is enough. Use for product relighting (studio softbox → window light), portrait mood shift (overcast → golden hour), or color-grade change....
creativeimagemedia