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Hyperflow

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jeremylongshore
hyperflow

Use when applying Hyperflow's orchestration doctrine in Codex, Antigravity, Grok, or another single-agent surface. Auto-invoke for non-trivial engineering work: build, implement, add, refactor, debug, fix, review, audit, plan, scope, design, brainstorm, ship, or deploy. Trigger with /hyperflow:hyperflow, "use hyperflow", "apply the doctrine", or automatically on any task-shaped message.

Overview

Publisherjeremylongshore
Repositorytons-of-skills-marketplace
Skill namehyperflow
Stars
2.8K
Forks
402
Bundled files
36
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.

  • 36 bundled files

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

  • Open source

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

Installation

Install the Hyperflow 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/hyperflow .claude/skills/hyperflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hyperflow 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 Hyperflow 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 Hyperflow 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.

Hyperflow Doctrine (single-agent port)

Apply Hyperflow's behavioral floor in surfaces that load skills but do not provide the full Claude Code multi-agent runtime.

Runtime Adaptation

Codex, OpenCode, Antigravity, and Grok often run one foreground agent (or a host-specific subagent API). Where the full doctrine says to dispatch parallel workers under reviewers:

  • Prefer the host's subagent API when it exists (Codex spawn, OpenCode Task, Grok spawn_subagent).
  • Otherwise do the work yourself, one coherent batch at a time.
  • Self-review each batch before moving on.
  • Run a final integration self-review over the cumulative diff.
  • Preserve the same autonomy, clarification, commit cadence, file-first artefact, no-attribution, and security rules.

Portable Function Router (Codex / OpenCode / Grok)

These hosts load Hyperflow as skills, not as native Claude-style slash commands. Treat these user messages as function aliases and execute the matching skill workflow inline in the current thread:

User saysRun
/hyperflow:plan, hyperflow plan, design with hyperflow, decompose with hyperflowplan
/hyperflow:dispatch, hyperflow dispatch, run the hyperflow plandispatch
/hyperflow:workflow, hyperflow workflow, run a workflowworkflow
/hyperflow:trace, hyperflow trace, debug with hyperflowtrace
/hyperflow:audit, hyperflow audit, review with hyperflowaudit
/hyperflow:deploy, hyperflow deploy, ship with hyperflowdeploy
/hyperflow:cache, hyperflow cachecache
/hyperflow:status, hyperflow statusstatus
/hyperflow:sticky, hyperflow stickysticky
/hyperflow:bridge, hyperflow bridgebridge
/hyperflow:flush, hyperflow flushflush
/hyperflow:background, hyperflow backgroundbackground
/hyperflow:scaffold, hyperflow scaffoldscaffold

Do not answer that /hyperflow:* is an unknown command on these surfaces. Strip the alias, load the matching skills/<name>/SKILL.md, and follow its workflow. If that workflow says to use unavailable Claude Code tools (Agent, Skill, or AskUserQuestion), emulate them: do worker/reviewer steps inline with visible labels, continue chained skills inline, and use the interaction fallback below when a structured question UI is missing.

Subagents And Auto-Chain

Codex

When Codex exposes multi-agent tools, map Hyperflow agent dispatches to Codex subagents instead of falling back to inline work:

  • Hyperflow Agent worker/searcher/writer calls map to Codex worker or explorer subagents.
  • If the callable tool is named multi_agent_v1.spawn_agent, use agent_type: worker for implementer/writer execution and agent_type: explorer for search/codebase-research tasks, then collect results before review.
  • Spawn independent sibling workers together when the runtime supports parallel subagent calls.
  • Every agent runs on the current session model — do not switch models per role. Match reasoning effort to task complexity: low for trivial docs/config checks, medium for normal planning/review, high for debugging, architecture, security, or final integration review.
  • Never request or default to xhigh.

When Codex does not expose subagent tools in the current session, use the single-agent port above: execute worker/reviewer phases inline with clear labels and continue.

Grok

Grok CLI / Grok Build loads skills from ~/.grok/skills/, project .grok/skills/, and compatible Claude/Cursor skill dirs. Project rules come from AGENTS.md / CLAUDE.md and .grok/rules/. Runtime signal often includes GROK_AGENT=1.

When Grok exposes spawn_subagent, map Hyperflow dispatches as follows:

Hyperflow roleGrok subagent_type
implementer / writer / general workergeneral-purpose
searcher / codebase researchexplore
plan-only research (no file writes)plan
domain specialists (architect, security-reviewer, …)matching type if registered; else general-purpose with the specialist charter in the prompt
  • Spawn independent sibling workers together when the runtime supports parallel subagent calls.
  • If subagents are disabled (GROK_SUBAGENTS=0 or config), run worker/reviewer phases inline with clear labels.
  • Prefer the native AskUserQuestion tool for structural gates when available.
  • Every agent runs on the current session model — no per-role model selection.
  • Do not invent Claude Code Agent tool calls; use spawn_subagent or inline work.

Auto-chain (all portable hosts)

For /hyperflow:workflow, use the portable workflow adapter (Codex / OpenCode / Grok branches in the workflow skill) instead of falling back to scope: research and planning, .hyperflow/tasks/ progress tracking when needed, parallel subagents when exposed, inline worker/reviewer phases otherwise, adversarial verification, quality gates, per-task conventional commits, and final synthesis. Do not describe this as native Claude Code dynamic workflow support.

These hosts may not expose Claude Code's Skill handoff tool. Treat every Hyperflow handoff as an inline auto-chain:

  • plan runs amplify → design → decompose inline, then stops at its build-location gate (always asked). It never auto-implements: on "this session" it continues into dispatch inline; on "another session" it writes a handoff package; on "stop" it keeps the plan.
  • dispatch offers audit and deploy structural gates, then runs the selected follow-up inline.
  • audit fix gates continue into plan with the generated audit-fix task (which then stops at its own build-location gate).

Do not stop with "Skill tool unavailable". Auto-chain is a behavior contract, not a host API requirement.

Interaction Fallback

When a host lacks a structured question UI (or AskUserQuestion is unavailable), do not skip the question or silently choose the recommended option. Render the same structural gate as a concise chat block and wait for the user's answer:

text
Hyperflow Question
<question>

1. <recommended option> (Recommended) — <short consequence>
2. <option> — <short consequence>

Use this fallback for every required clarification or structural gate: Amplify handoff, Spec chain mode, Spec brainstorming questions, Scope ambiguity questions, Dispatch audit/deploy gates, Audit fix gate, Deploy commit-inclusion and push gates, and any security/irreversibility escalation. It is still banned to ask invented confirmation questions such as "should I proceed?".

On Grok, prefer the native AskUserQuestion tool when present; use the chat-block fallback only if that tool is missing.

Reasoning Policy

  • Every agent runs on the current session model — there is no per-role model selection.
  • Resolve reasoning effort by task/profile: low for trivial docs/config checks, medium for normal planning/review, and high for debugging, architecture, security, and final integration.
  • Never default portable hosts to exotic max-effort modes (e.g. Codex xhigh).

Core Rules

  1. Execute task-shaped requests without confirmation.
  2. Clarify only after reading the relevant code and only for genuine ambiguity.
  3. Keep long-form plans, specs, task decompositions, and audits under .hyperflow/.
  4. Use conventional commits, one distinct user task per commit.
  5. Never reference the model as the actor in commits, docs, comments, task files, or memory.
  6. Respect the security blocklist in security.md.

Workflow Routing

IntentWorkflow
brainstorm, design, explore, "should we"Research first, ask material questions, then propose approaches
scope, decompose, "plan out"Map affected files, then write a task graph under .hyperflow/tasks/
big task, large migration, repo-wide audit, run a workflow, dynamic workflowUse the workflow skill: Claude Code native workflow, or Codex/OpenCode/Grok portable adapter, otherwise decompose through scope
build, implement, add, refactorDecompose, execute batches, self-review, commit per task
debug, fix it, "why is X failing"Root-cause before patching
audit, review, "check for issues"Review findings first, then offer/apply fixes
ship, push, release, deployRun gates, commit/release, ask before push

For full multi-agent doctrine, read DOCTRINE.md and the linked reference files in this directory.

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 Hyperflow AI skill do?

Use when applying Hyperflow's orchestration doctrine in Codex, Antigravity, Grok, or another single-agent surface. Auto-invoke for non-trivial engineering work: build, implement, add, refactor, debug, fix, review, audit, plan, scope, design, brainstorm, ship, or deploy. Trigger with /hyperflow:hyperflow, "use hyperflow", "apply the doctrine", or automatically on any task-shaped message.

Why use Hyperflow on TypingMind?

Because you install it once and use it with any model. Hyperflow 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 Hyperflow 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/hyperflow. 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 Hyperflow?

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 Hyperflow?

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

Is the Hyperflow 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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