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Workflow Orchestrator logo

Workflow Orchestrator

Organization
adobe
workflow-orchestrator

Orchestrate complete lifecycle work for the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM as a Cloud Service, from design and implementation through validation, release readiness, and incident troubleshooting.

Overview

Publisheradobe
Repositoryskills
Skill nameworkflow-orchestrator
Stars
298
Forks
92
Bundled files
11
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by adobe on GitHub. Read the source before you install it.

Installation

Install the Workflow Orchestrator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/dispatcher/workflow-orchestrator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/adobe/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/aem/cloud-service/skills/dispatcher/workflow-orchestrator .claude/skills/workflow-orchestrator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Workflow Orchestrator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Workflow Orchestrator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Workflow Orchestrator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Dispatcher Workflow Orchestrator (Cloud)

Use this skill when users need end-to-end Dispatcher support instead of a single specialist workflow.

Scope

  • Full lifecycle orchestration for cloud Dispatcher work:
    • requirements and design
    • config implementation and hardening
    • filter, cache, rewrite, vhost, and farm design
    • feature-specific flows such as /auth_checker, vanity URLs, GraphQL/CORS, Commerce proxy routes, frontend-static passthrough, and Dynamic Media delivery passthrough
    • static/runtime validation
    • release readiness and rollback planning
    • production incident triage

Routing Model

  1. Start in config-authoring for file design and edits.
  2. Pull in technical-advisory for policy, documentation, cloud guardrails, and evidence planning.
  3. Pull in security-hardening and performance-tuning for non-functional risk checks and environment-sensitive review.
  4. Switch to incident-response for live failures, probe regressions, cache anomalies, or validator/runtime mismatches.
  5. Return a single consolidated output: changes, evidence, risk, rollback, and follow-ups.

Operational Packaging

Use these shared references to keep broad requests deterministic:

  1. Start with quick-start-execution-path.md when the user is new, the repo root is ambiguous, or the request spans multiple concerns.
  2. Normalize the repo to a dispatcher src root with repo-layout-workflows.md.
  3. Convert the chosen specialist playbook into exact MCP commands with playbook-command-linkage.md.
  4. Use the specialist skill references only after the path above is fixed.

Entry Criteria

Use when user intent is any of:

  • end-to-end implementation
  • pre-release readiness review
  • troubleshooting + fix + re-validation in one flow
  • broad audit across config, security, and performance
  • complete cloud-service dispatcher development from new feature to release gate
  • “single point of development” requests that span authoring, validation, troubleshooting, and hardening

Exit Criteria

Always return:

  • touched files and why
  • executed checks (static + runtime) and evidence
  • selected scenario/playbook path
  • unresolved risks/gaps
  • rollback trigger + rollback action
  • next-step plan if prerequisites blocked verification

Related Skills

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Workflow Orchestrator AI skill do?

Orchestrate complete lifecycle work for the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM as a Cloud Service, from design and implementation through validation, release readiness, and incident troubleshooting.

Why use Workflow Orchestrator on TypingMind?

Because you install it once and use it with any model. Workflow Orchestrator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Workflow Orchestrator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/dispatcher/workflow-orchestrator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Workflow Orchestrator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Workflow Orchestrator?

As many as you like. As long as a model supports skills, you can use Workflow Orchestrator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Workflow Orchestrator AI skill free?

Yes. It is published on GitHub by adobe under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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