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workflow-coordinator工作流程协调员

Agent Skill

workflow-coordinator 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

250

周安装

10

GitHub Stars

5

下载量

81
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

2

许可证

unknown

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:workflow-coordinator(工作流程协调员)
来源仓库:https://github.com/dangeles/claude
仓库路径:skills/workflow-coordinator
安装命令:
npx skills add https://github.com/dangeles/claude --skill workflow-coordinator
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/dangeles/claude --skill workflow-coordinator

简介

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 支持基于关键词、任务场景或来源线索进行信息筛选,适用于流程协调与信息管理场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限与维护状态。
  • 安装前建议核实是否会触发联网、命令执行或文件读写操作。
  • 可结合原始 README 进一步了解具体用法和功能边界。

SKILL.md

Workflow Coordinator

Universal cross-workflow handoff coordination using schema v3.0.

When to Use

  • Coordinating handoffs between independent workflows (e.g., skill-editor to programming-pm)
  • Discovering available target workflows for a handoff
  • Validating handoff payloads before transmission
  • Debugging multi-hop handoff chains via distributed tracing
  • Adding handoff support to a new or existing skill

When NOT to Use

  • Internal specialist handoffs within programming-pm (use internal v1.2 schema)
  • Simple file passing between agents (no schema validation needed)
  • Single-skill invocations (no coordination needed)
  • Agent team coordination within a single task (use agent teams directly)

Pilot Scope Limitations

This is v3.0 pilot (documentation + schema artifacts only):

  • Token counting: Guidance-only (heuristic estimation via characters / 4, not tiktoken)
  • Schema validation: Manual invocation required (python3 one-liner)
  • Circular handoff detection: Advisory, not automated
  • CLI tools: Deferred to v1.1 (claude-handoff validate, etc.)
  • Adapter layer: Deferred to v1.1 (cross-version schema translation)
  • Registry sync tool: Deferred to v1.1 (claude-handoff-registry sync)

Quick Start: Minimal Handoff

The absolute minimum v3.0 handoff (5 required top-level fields):

{
  "handoff": {
    "version": "3.0",
    "schema_type": "universal",
    "timestamp": "2026-02-07T18:30:00Z",
    "trace_id": "550e8400-e29b-41d4-a716-446655440000",
    "source": {
      "skill": "skill-editor",
      "workflow_id": "session-20260207-183000",
      "session_path": "/tmp/skill-editor-session/session-20260207-183000",
      "phase": "Phase 3"
    },
    "target": {
      "skill": "programming-pm"
    },
    "context": {
      "summary": "Implement workflow coordination system",
      "problem_type": "implementation"
    },
    "payload": {
      "working": {
        "description": "Key implementation details here"
      }
    },
    "meta": {
      "token_count": 250,
      "confidence": "high"
    }
  }
}

Generate a trace_id:

python3 -c "import uuid; print(uuid.uuid4())"

Estimate token count:

wc -c < handoff.json | awk '{printf "Estimated tokens: %d\n", $1/4}'

Handoff Lifecycle

Sender (Source Workflow)

  1. Determine that work should be handed off to another workflow
  2. Discover available target workflows (see Reference Documents below)
  3. Present target options to user for selection (or auto-select if only one match)
  4. Generate trace_id (UUID v4) if this is a new trace, or propagate existing
  5. Build handoff payload using tiered context structure:

- payload.working (<500 tokens): Immediate context needed by target - payload.session (<1000 tokens): Session artifacts and state (optional) - payload.references (<500 tokens): File paths for on-demand loading (optional)

  1. Estimate token count via characters / 4 heuristic
  2. If over 2000 tokens, apply compression strategies (see validation reference)
  3. Validate against schema v3.0 (python3 -c "import json, jsonschema;...")
  4. Write handoff file to {session_path}/handoffs/{source}-to-{target}-{timestamp}.json
  5. Log handoff transmission event to trace.jsonl

Receiver (Target Workflow)

  1. Read handoff file from provided path
  2. Validate handoff.version is "3.0" (or handle legacy gracefully)
  3. Extract trace_id and propagate to own session state
  4. Read context.summary and context.problem_type for initial orientation
  5. Load payload.working into working context
  6. Optionally load payload.session and payload.references as needed
  7. Begin processing at target.expected_phase (if specified) or entry point

Reference Documents

Load the relevant reference for your task:

TaskReference
Creating a handoff payloadreferences/handoff-validation.md
Debugging a handoff chainreferences/distributed-tracing.md
Finding target workflowsreferences/handoff-registry.md
Adding handoff support to a skillreferences/frontmatter-metadata-standard.md
Schema definition (JSON Schema)references/universal-handoff-schema-v3.0.json

Load only the reference you need -- progressive disclosure keeps context lean.


Design Decisions

Key architectural decisions (captured from perspective-swarm analysis and synthesis):

  1. Hybrid distributed orchestration (not master orchestrator) -- Each workflow is autonomous; coordinator provides schema and conventions, not control
  2. Extend perspective-swarm v2.0 (not start from scratch) -- v2.0 already implements research-recommended patterns (JSON Schema, workflow discovery)
  3. 2000-token budget (research-based, configurable) -- Research shows 3-5x cost multiplier for context bloat; fixed budget with tiered structure
  4. JSON Schema Draft 2020-12 (OpenAPI 3.1 compatible) -- Industry standard with unevaluatedProperties for extensibility
  5. File-based tracing (not database-backed) -- Lightweight, no infrastructure dependencies, JSON Lines format
  6. unevaluatedProperties: false for schema extensibility -- Recognizes properties from all subschemas unlike additionalProperties, enabling v2.0/v3.0 coexistence (Strangler Fig migration)

Examples

Two complete example handoff files demonstrate the schema:

  • examples/skill-editor-to-programming-pm.json -- Full v3.0 handoff with all sections (skill-editor hands off implementation work)
  • examples/programming-pm-to-skill-editor.json -- Reverse direction (programming-pm requests new skill creation)

Both examples validate against references/universal-handoff-schema-v3.0.json.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

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

Codex

37.02%
按下载量换算30

Claude

28.72%
按下载量换算23

Cursor

19.54%
按下载量换算16

Gemini CLI

10.54%
按下载量换算9

安全审计

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通过

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通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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