Hyperflow Plan

CommunityPopular

jeremylongshore

hyperflow-plan

Hyperflow planning phase. Use when a request needs shaping before code — a rough prompt to sharpen, an ambiguous idea to design, or a clear-enough task to decompose. Verbs like plan, design, brainstorm, explore, "should we", "what's the best way to", scope, decompose, "plan out", "break down", "enhance this prompt". Thinking, not building. Writes an optional spec to .hyperflow/specs/<slug>.md and a task file to .hyperflow/tasks/<slug>.md, then hands off to hyperflow-dispatch.

Overview

Publisher	jeremylongshore
Repository	`tons-of-skills-marketplace`
Skill name	`hyperflow-plan`
Stars	2.8K
Forks	402
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 Hyperflow Plan AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/hyperflow/templates/antigravity/skills/hyperflow-plan

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/templates/antigravity/skills/hyperflow-plan .claude/skills/hyperflow-plan

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hyperflow Plan 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 Plan 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 Plan 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-plan — planning phase (Antigravity single-agent)

Thinking, not building. The only writes are to .hyperflow/. Each phase skips itself when the request doesn't need it. Follow the hyperflow doctrine (autonomy, file-first, AskUserQuestion gates).

Steps

Amplify (skippable). If the prompt is rough, rewrite it into its strongest form — role · task · context · constraints · output spec. Skip when it's already specific. Never inflate a one-line ask into a spec.
Research first. Read the relevant code, AGENTS.md, and .hyperflow/memory/*. Map the affected surface yourself — do not ask what the code answers.
Design (skippable). For an open-ended request: ask ≥2 clarifying questions (what/which/where only), propose 2–3 approaches, then design section-by-section into .hyperflow/specs/<slug>.md with approval per section. A clear request bounces straight to decomposition. When a system, UI, motion, or mobile surface is in scope, ground the design in the matching standards (architecture decomposition + a diagram, the design system, the Motion language, the mobile platform/device matrix).
Decompose. Produce a topologically-ordered batch graph; each sub-task = one conventional-commit-sized change. Split any sub-task touching >5 files, >500 LOC, 2+ subsystems, or >10-min review. Write .hyperflow/tasks/<slug>.md: status table → Goal → Why → Scope-at-a-glance → Affected files → Execution plan → Batches (role, files, complexity, acceptance criteria, commit stub) → Verification plan.
Print Plan ready — .hyperflow/tasks/<slug>.md (N batches, M sub-tasks).
Hand off: invoke the hyperflow-dispatch skill with the task slug — or, in two-session mode, write a committed handoff package and stop.

Rules

No implementation code; no source edits.
Floor of 2 clarifying questions on the design path; 0–3 on the bounce (decompose-only) path.
Single-batch plans for multi-file work are an anti-pattern — decompose.
Always include a concrete verification plan.

Frequently asked questions

What does the Hyperflow Plan AI skill do?

Why use Hyperflow Plan on TypingMind?

Because you install it once and use it with any model. Hyperflow Plan 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 Plan 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/templates/antigravity/skills/hyperflow-plan. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hyperflow Plan?

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 Plan?

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

Is the Hyperflow Plan 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

hyperflow-plan — planning phase (Antigravity single-agent)

Steps

Rules

Frequently asked questions

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