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fal-workflow错误工作流程

Agent Skill

fal-workflow 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

885

周安装

38

GitHub Stars

85

下载量

310
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:fal-workflow(错误工作流程)
来源仓库:https://github.com/ilkerzg/agent-skills
仓库路径:skills/fal-workflow
安装命令:
npx skills add https://github.com/ilkerzg/agent-skills --skill fal-workflow
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/ilkerzg/agent-skills --skill fal-workflow

简介

用于查找、检索和筛选相关信息,支持复杂 AI 工作流构建。

  • 适合在关键词或场景驱动下快速定位候选结果与来源线索。
  • 需结合原始 README 验证具体用法,注意可能的联网与文件操作。
  • 安装前建议确认权限范围和维护状态,避免非预期系统交互。
  • fal-workflow 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

fal.ai Workflow Generator

Generate 100% working, production-ready fal.ai workflow JSON files. Workflows chain multiple AI models together for complex generation pipelines.

References:

Troubleshooting Reference:

  • Complete Workflows - Working JSON examples for debugging (use ONLY when user reports errors)

Core Architecture

Valid Node Types

⚠️ ONLY TWO VALID NODE TYPES EXIST:

TypePurpose
"run"Execute a model/app
"display"Output results to user

❌ INVALID: type: "input" - This does NOT exist! Input is defined ONLY in schema.input.

Minimal Working Example

{
  "name": "my-workflow",
  "title": "My Workflow",
  "contents": {
    "name": "workflow",
    "nodes": {
      "output": {
        "type": "display",
        "id": "output",
        "depends": ["node-image"],
        "input": {},
        "fields": { "image": "$node-image.images.0.url" }
      },
      "node-image": {
        "type": "run",
        "id": "node-image",
        "depends": ["input"],
        "app": "fal-ai/flux/dev",
        "input": { "prompt": "$input.prompt" }
      }
    },
    "output": { "image": "$node-image.images.0.url" },
    "schema": {
      "input": {
        "prompt": {
          "name": "prompt",
          "label": "Prompt",
          "type": "string",
          "required": true,
          "modelId": "node-image"
        }
      },
      "output": {
        "image": { "name": "image", "label": "Generated Image", "type": "string" }
      }
    },
    "version": "1",
    "metadata": {
      "input": { "position": { "x": 0, "y": 0 } },
      "description": "Simple text to image workflow"
    }
  },
  "is_public": true,
  "user_id": "",
  "user_nickname": "",
  "created_at": ""
}

Reference Syntax

ReferenceUse CaseExample
$input.fieldInput value$input.prompt
$node.outputLLM text output$node-llm.output
$node.images.0.urlFirst image URL$node-img.images.0.url
$node.image.urlSingle image URL$node-upscale.image.url
$node.video.urlVideo URL$node-vid.video.url
$node.audio_file.urlAudio URL$node-music.audio_file.url
$node.frame.urlExtracted frame$node-extract.frame.url

CRITICAL: No String Interpolation

⚠️ NEVER mix text with variables! Variable MUST be the ENTIRE value.

// ❌ WRONG - WILL BREAK
"prompt": "Create image of $input.subject in $input.style"

// ✅ CORRECT - Variable is the ENTIRE value
"prompt": "$input.prompt"
"prompt": "$node-llm.output"

To combine values: Use fal-ai/text-concat or fal-ai/workflow-utilities/merge-text. See Model Reference.


Critical Rules

C1: Dependencies Must Match References

// ❌ WRONG
"node-b": {
  "depends": [],
  "input": { "data": "$node-a.output" }
}

// ✅ CORRECT
"node-b": {
  "depends": ["node-a"],
  "input": { "data": "$node-a.output" }
}

C2: ID Must Match Object Key

// ❌ WRONG
"my-node": { "id": "different-id" }

// ✅ CORRECT
"my-node": { "id": "my-node" }

C3: Use Correct LLM Type

  • openrouter/router → Text only, no image_urls
  • openrouter/router/vision → ONLY when analyzing images

C4: Schema modelId Required

"schema": {
  "input": {
    "field": { "modelId": "first-consuming-node" }
  }
}

C5: Output Depends on All Referenced Nodes

"output": {
  "depends": ["node-a", "node-b", "node-c"],
  "fields": {
    "a": "$node-a.video",
    "b": "$node-b.images.0.url"
  }
}


Quick Reference Card

Output References

Model TypeOutput Reference
LLM$node.output
Text Concat$node.results
Merge Text$node.text
Image Gen (array)$node.images.0.url
Image Process (single)$node.image.url
Video$node.video.url
Music$node.audio_file.url
Frame Extract$node.frame.url

Use search-models.sh or search_models MCP tool to discover current models. See references/MODELS.md for workflow code templates.


Input Schema

"schema": {
  "input": {
    "text_field": {
      "name": "text_field",
      "label": "Display Label",
      "type": "string",
      "description": "Help text",
      "required": true,
      "modelId": "consuming-node"
    },
    "image_urls": {
      "name": "image_urls",
      "type": { "kind": "list", "elementType": "string" },
      "required": true,
      "modelId": "node-id"
    }
  }
}

Pre-Output Checklist

Before outputting any workflow, verify:

  • ⚠️ All nodes have type: "run" or type: "display" ONLY (NO type: "input"!)
  • ⚠️ No string interpolation - variable MUST be ENTIRE value
  • Every $node.xxx has matching depends entry
  • Every node id matches object key
  • Input schema has modelId for each field
  • Output depends on ALL referenced nodes
  • Correct LLM type (router vs router/vision)

Usage

Using Script

bash /mnt/skills/user/fal-workflow/scripts/create-workflow.sh \
  --name "my-workflow" \
  --title "My Workflow Title" \
  --nodes '[...]' \
  --outputs '{...}'

Using MCP Tool

mcp__fal-ai__create-workflow({
  smartMode: true,
  intent: "Generate a story with LLM, create an illustration, then animate it"
})

Troubleshooting

Invalid Node Type Error (MOST COMMON)

Error: unexpected value; permitted: 'run', 'display', field required

Cause: You created a node with type: "input" which does NOT exist. Solution: Remove ANY node with type: "input". Define input fields ONLY in schema.input.

Dependency Error

Error: Node references $node-x but doesn't depend on it

Solution: Add the referenced node to the depends array.

ID Mismatch Error

Error: Node key "my-node" doesn't match id "different-id"

Solution: Ensure the object key matches the id field exactly.

LLM Vision Error

Error: image_urls provided but using text-only router

Solution: Switch to openrouter/router/vision when analyzing images.


Finding Model Schemas

Every model's input/output schema:

https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=[endpoint_id]

Example:

https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/nano-banana-pro

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.66%
按下载量换算83

Gemini CLI

23.65%
按下载量换算73

Codex

19.37%
按下载量换算60

Antigravity

12.3%
按下载量换算38

OpenCode

7.56%
按下载量换算23

Cursor

3.25%
按下载量换算10

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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