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Workflow

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jeremylongshore
workflow

Use when a task is too large for turn-by-turn orchestration and should run through the big-task workflow lane: system-wide changes, large migrations, repo-wide audits, high-confidence verification, or tasks explicitly asking to run a workflow. Claude Code uses native dynamic workflows; Codex, OpenCode, and Grok use the portable workflow adapter. Trigger with /hyperflow:workflow, "run a workflow", "dynamic workflow", "big task", "large migration", "repo-wide audit".

Overview

Publisherjeremylongshore
Repositorytons-of-skills-marketplace
Skill nameworkflow
Stars
2.8K
Forks
402
Bundled files
Instructions only
LicenseMIT
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Workflow 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.
  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/jeremylongshore/tons-of-skills-marketplace.git /tmp/tons-of-skills-marketplace
mkdir -p .claude/skills
cp -r /tmp/tons-of-skills-marketplace/plugins/ai-agency/hyperflow/skills/workflow .claude/skills/workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Workflow 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 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 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.

Workflow

Big-task path for work that is too large for normal turn-by-turn orchestration: system-wide changes, large migrations, repo-wide audits, high-confidence verification, and task prompts that explicitly ask for a workflow.

  • In Claude Code, use the host dynamic workflow runtime.
  • In Codex, run the portable workflow adapter with Codex subagents when exposed; otherwise run the same phases inline in the current thread.
  • In OpenCode, run the portable workflow adapter with Task/subagent dispatch when exposed; otherwise run the same phases inline in the current session.
  • In Grok, run the portable workflow adapter with spawn_subagent when enabled; otherwise run the same phases inline in the current session.
  • In Antigravity, Desktop/web bridge mode, or any host that cannot preserve the adapter phases, say so in one line and route to /hyperflow:plan with chain-mode=auto.

Claude Code dynamic workflows require Claude Code v2.1.154 or later and can be disabled by /config, managed settings, ~/.claude/settings.json, or CLAUDE_CODE_DISABLE_WORKFLOWS=1. When disabled, use the portable adapter if the host is Codex, OpenCode, or Grok; otherwise route to /hyperflow:plan with chain-mode=auto.

Routing Rules

  • Run this skill in Claude Code, Codex, OpenCode, and Grok.
  • Auto-route here when triage returns flow=deep or flow=scientific, scope=system-wide, or the user says big task, large migration, repo-wide audit, run a workflow, or dynamic workflow.
  • Do not route here for moderate multi-file work, routine bug fixes, or a task that needs user sign-off between implementation stages. Big-task workflow runs should not depend on arbitrary mid-run user input; split sign-off-heavy work into separate workflows or use spec -> scope -> dispatch.
  • Do not set /effort ultracode or xhigh automatically. The user can enable /effort ultracode manually for session-wide workflow selection.

Provider Contracts

Claude Code Native Workflow

When this skill runs, ask the Claude Code workflow runtime to create a dynamic workflow for $ARGUMENTS. The generated workflow must preserve Hyperflow's doctrine inside the worker prompts and must include these phases:

  1. Research and planning

    • Map affected files, dependency edges, tests, docs, and risk boundaries.
    • Read .hyperflow/profile.md, .hyperflow/architecture.md, .hyperflow/conventions.md, .hyperflow/testing.md, and .hyperflow/memory/index.md when present.
    • Produce a concise execution graph with parallelizable units and dependencies.
  2. Parallel implementation or investigation

    • Fan out independent agents by subsystem or file family.
    • Keep each agent brief specific: objective, files in scope, constraints, acceptance criteria, and test expectations.
    • Use the lightest model/stage that can safely do the work when the runtime supports model routing.
  3. Adversarial verification

    • Run independent verification agents against each implementation or finding.
    • For audits, verify each finding before reporting it.
    • For implementation, check cross-file integration, regression risk, security-sensitive paths, and missed tests.
  4. Quality gates and repair loop

    • Run the project lint, typecheck, build, and relevant tests from .hyperflow/testing.md or detected package scripts.
    • Retry focused fixes only for verified failures.
    • Never use --no-verify; never force-push to main or master.
  5. Final synthesis

    • Return one coordinated result with completed work, verification evidence, unresolved risks, changed files, and next actions.
    • For durable project learnings, identify what should be appended to .hyperflow/memory/, but do not invent memory entries unrelated to the run.

Codex Portable Workflow Adapter

Codex does not provide Claude Code's dynamic workflow runtime. Treat /hyperflow:workflow as a custom Hyperflow workflow envelope around Codex subagents and inline fallback:

  1. Research and planning

    • Read the same .hyperflow/ cache files listed above when present.
    • Write or update .hyperflow/tasks/<slug>.md for implementation or audit work that needs durable progress tracking.
    • Build an execution graph with parallelizable units, dependencies, expected commits, and verification commands.
  2. Parallel implementation or investigation

    • If Codex subagent tools are exposed, dispatch independent searcher/worker/writer units together and collect their results before review.
    • Map implementation and writing tasks to worker subagents; map codebase research to explorer/search subagents.
    • If subagents are unavailable, run each unit inline with explicit worker and reviewer labels.
  3. Adversarial verification

    • Run a separate verification pass for each completed unit before reporting it.
    • Use Codex thinking defaults for verification and final integration review.
  4. Quality gates and commits

    • Run the detected lint, typecheck, build, and relevant tests.
    • Commit each accepted unit separately using conventional commits.
    • Never use --no-verify; never request xhigh.
  5. Final synthesis

    • Return changed files, verification evidence, unresolved risks, and next actions.

OpenCode Portable Workflow Adapter

OpenCode does not provide Claude Code's dynamic workflow runtime. Treat /hyperflow:workflow as a custom Hyperflow workflow envelope around OpenCode's task/subagent facilities and inline fallback:

  1. Research and planning

    • Read the same .hyperflow/ cache files listed above when present.
    • Write or update .hyperflow/tasks/<slug>.md for implementation or audit work that needs durable progress tracking.
    • Build an execution graph with parallelizable units, dependencies, expected commits, and verification commands.
  2. Parallel implementation or investigation

    • If OpenCode exposes Task/subagent dispatch, send independent implementation or investigation units through that path.
    • Keep each subtask bounded by objective, files in scope, constraints, acceptance criteria, and tests.
    • If task dispatch is unavailable, run each unit inline with explicit worker and reviewer labels.
  3. Adversarial verification

    • Run a separate verification pass for each completed unit before reporting it.
    • Run verification and the final integration review as decision-agent passes on the current session model.
  4. Quality gates and commits

    • Run the detected lint, typecheck, build, and relevant tests.
    • Commit each accepted unit separately using conventional commits.
    • Never use --no-verify.
  5. Final synthesis

    • Return changed files, verification evidence, unresolved risks, and next actions.

Grok Portable Workflow Adapter

Grok does not provide Claude Code's dynamic workflow runtime. Treat /hyperflow:workflow as a custom Hyperflow workflow envelope around Grok spawn_subagent and inline fallback:

  1. Research and planning

    • Read the same .hyperflow/ cache files listed above when present.
    • Write or update .hyperflow/tasks/<slug>.md for implementation or audit work that needs durable progress tracking.
    • Build an execution graph with parallelizable units, dependencies, expected commits, and verification commands.
  2. Parallel implementation or investigation

    • If spawn_subagent is available and subagents are not disabled (GROK_SUBAGENTS / config), dispatch independent units together:
      • implementer/writer → subagent_type: general-purpose
      • searcher/research → subagent_type: explore
    • Collect results before review; spawn independent siblings in parallel when the runtime allows.
    • If subagents are unavailable, run each unit inline with explicit worker and reviewer labels.
  3. Adversarial verification

    • Run a separate verification pass for each completed unit before reporting it.
    • Run verification and the final integration review as decision-agent passes on the current session model.
  4. Quality gates and commits

    • Run the detected lint, typecheck, build, and relevant tests.
    • Commit each accepted unit separately using conventional commits.
    • Never use --no-verify.
  5. Final synthesis

    • Return changed files, verification evidence, unresolved risks, and next actions.

Claude Code Prompt Skeleton

Use this shape when handing the task to the workflow runtime:

text
Create a dynamic workflow for this Hyperflow big-task run.

Task:
<user task>

Doctrine:
- Preserve Hyperflow autonomy: execute reversible work without invented confirmations.
- Ask only for genuine ambiguity after codebase research.
- Keep plans, task decompositions, audits, and memory under .hyperflow/ when files are needed.
- Use conventional commits, one distinct task per commit.
- Never use --no-verify and never force-push to main/master.
- Respect the Hyperflow security blocklist in skills/hyperflow/security.md.

Required phases:
1. Research and planning.
2. Parallel implementation or investigation.
3. Adversarial verification.
4. Quality gates and focused repair loop.
5. Final synthesis.

Acceptance:
- Every substantive result is independently checked before being reported.
- Quality gates run or are explicitly marked unavailable with the command attempted.
- The final answer includes evidence, changed files, unresolved risks, and next actions.

Save For Reuse

When a run succeeds and the user will repeat it, mention that Claude Code can save the generated workflow from /workflows with s. Project workflows save under .claude/workflows/; personal workflows save under ~/.claude/workflows/. Do not create those files directly from this skill because plugin packaging does not currently ship .claude/workflows/ as a first-class component.

Codex, OpenCode, and Grok adapters are not saved through /workflows; repeatable behavior comes from this skill, .hyperflow/tasks/, project memory, and provider-specific subagent/task configuration.

Frequently asked questions

What does the Workflow AI skill do?

Use when a task is too large for turn-by-turn orchestration and should run through the big-task workflow lane: system-wide changes, large migrations, repo-wide audits, high-confidence verification, or tasks explicitly asking to run a workflow. Claude Code uses native dynamic workflows; Codex, OpenCode, and Grok use the portable workflow adapter. Trigger with /hyperflow:workflow, "run a workflow", "dynamic workflow", "big task", "large migration", "repo-wide audit".

Why use Workflow on TypingMind?

Because you install it once and use it with any model. Workflow 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 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/hyperflow/skills/workflow. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Workflow?

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?

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

Is the Workflow AI skill free?

Yes. It is published on GitHub by jeremylongshore under the MIT 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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