Agent Skills › vixues/LeAgent › workflow-helper

workflow-helper

GitHub

提供工作流设计与自动化指南，涵盖目标定义、步骤拆解、工具映射及错误处理。支持顺序、并行、条件等模式，指导创建、运行和监控自动化任务管道，提升流程效率与可维护性。

backend/leagent/skills/builtin/workflow-helper/SKILL.md vixues/LeAgent

Trigger Scenarios

构建工作流管理自动化任务编排多工具协作设计数据流水线

Install

npx skills add vixues/LeAgent --skill workflow-helper -g -y

More Options

Non-standard path

npx skills add https://github.com/vixues/LeAgent/tree/main/backend/leagent/skills/builtin/workflow-helper -g -y

Use without installing

npx skills use vixues/LeAgent@workflow-helper

指定 Agent (Claude Code)

npx skills add vixues/LeAgent --skill workflow-helper -a claude-code -g -y

安装 repo 全部 skill

npx skills add vixues/LeAgent --all -g -y

预览 repo 内 skill

npx skills add vixues/LeAgent --list

SKILL.md

Frontmatter

{
    "name": "workflow-helper",
    "license": "Apache-2.0",
    "metadata": {
        "tags": [
            "workflow",
            "automation",
            "orchestration",
            "pipeline",
            "dag"
        ],
        "version": "1.0.0",
        "category": "automation"
    },
    "description": "Guidance for creating, managing and executing workflow automations that chain multiple tools and agents together. Use when the user asks about building, listing, running or composing workflows and automated task pipelines.",
    "allowed-tools": "workflow_list workflow_run workflow_status code_execution"
}

Workflow Helper

You are assisting with workflow design and automation. Follow these guidelines.

Workflow Design

Define the goal: what outcome should the workflow produce?
Identify steps: break the goal into discrete, ordered operations.
Map tools: select the right tool or agent for each step.
Plan data flow: what inputs each step needs and what outputs it produces.
Handle errors: decide on retry policy, fallbacks, and failure escalation.

Workflow Patterns

Sequential: Step A → Step B → Step C. Each step uses the previous step's output.
Parallel: Steps run concurrently when they have no dependencies.
Conditional: Branch based on intermediate results or user input.
Loop: Iterate over a collection with a consistent body.
Pipeline: Stream data through stages (extract → transform → load).

Common Operations

Creating a Workflow

Start from a clear problem statement and acceptance criteria.
Prefer reusing existing workflow templates before writing a new one.
Parameterize inputs so the workflow can be reused with different data.

Running and Monitoring

Present workflow status clearly: pending, running, succeeded, failed, paused.
Surface intermediate outputs so the user can diagnose stalled runs.
Respect cancel / pause signals and clean up subprocesses.

Integrating with Other Skills

Use load_skill to pull in a specialised skill when a step needs domain expertise.
Pass structured JSON between steps to keep data shape predictable.

Best Practices

Keep individual steps small and idempotent where possible.
Log meaningful progress updates — workflow runs can be long.
Document expected inputs, outputs, and failure modes near the workflow definition.
Use consistent naming conventions (snake_case for workflow IDs).
Test workflows with small, representative datasets before production runs.