Ralph Specum Refactor

Community

tzachbon

ralph-specum-refactor

This skill should be used only when the user explicitly asks to use `$ralph-specum-refactor`, or explicitly asks Ralph Specum in Codex to revise spec artifacts after implementation learnings.

Overview

Publisher	tzachbon
Repository	`smart-ralph`
Skill name	`ralph-specum-refactor`
Stars	559
Forks	50
Bundled files	1
License	MIT
Links	Skill source Repository

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by tzachbon on GitHub. Read the source before you install it.

Installation

Install the Ralph Specum Refactor 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.
https://github.com/tzachbon/smart-ralph/tree/main/plugins/ralph-specum-codex/skills/ralph-specum-refactor
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/tzachbon/smart-ralph/tree/main/plugins/ralph-specum-codex/skills/ralph-specum-refactor

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/tzachbon/smart-ralph.git /tmp/smart-ralph
mkdir -p .claude/skills
cp -r /tmp/smart-ralph/plugins/ralph-specum-codex/skills/ralph-specum-refactor .claude/skills/ralph-specum-refactor

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

Use it in TypingMind

Enable Ralph Specum Refactor 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 Ralph Specum Refactor 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 Ralph Specum Refactor 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.

Ralph Specum Refactor

You are a coordinator, not a refactor specialist -- delegate spec revision to a refactor-specialist sub-agent.

Contract

Resolve the active spec by explicit path, exact name, or .current-spec
Review files in order: requirements.md, design.md, tasks.md
Cascade downstream updates when upstream content changes
Reconcile activePrototypes and preserve unrelated refactor work

Action

Resolve the target spec.
Read .progress.md and existing spec files.
Run prototype_records.py reconcile whenever .ralph-state.json exists, including when activePrototypes is empty, then run select-downstream --state "$BASE_PATH/.ralph-state.json" --target "$FILE" --path "$FILE" with the resolved basePath. Stop a file's refactor when its targetDecisions entry is not both proofAvailable: true and eligible: true, including an active blocker, stale dependency, approved-transfer overlap, or unavailable proof.
When refactor returns to execution, restore taskIndex from the blocking entry's returnTaskIndex through merge_state.py before dispatch.
Delegate spec revision to a refactor-specialist sub-agent. Pass .progress.md, existing spec files, and implementation learnings. The sub-agent identifies what changed, what stayed accurate, and what is obsolete. Do NOT revise spec files yourself.
The sub-agent preserves newer Ralph concepts already expressed in the spec, including approval checkpoints, granularity choices, [P] tasks, [VERIFY] tasks, VE tasks, and epic constraints when relevant.
The sub-agent updates files in order:
- requirements.md
- design.md
- tasks.md
If requirements changed, revisit design and tasks.
If design changed, revisit tasks.
Record the rationale and cascade decisions in .progress.md.

Response Handoff

After revising spec files, name the files that changed and summarize the updates briefly.
End with exactly one explicit choice prompt:
- approve current artifact
- request changes
- continue to implementation
Treat continue to implementation as approval of the updated spec files.

Bundled files

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

agents/openai.yaml1 KB

Frequently asked questions

What does the Ralph Specum Refactor AI skill do?

This skill should be used only when the user explicitly asks to use `$ralph-specum-refactor`, or explicitly asks Ralph Specum in Codex to revise spec artifacts after implementation learnings.

Why use Ralph Specum Refactor on TypingMind?

Because you install it once and use it with any model. Ralph Specum Refactor 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 Ralph Specum Refactor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tzachbon/smart-ralph/tree/main/plugins/ralph-specum-codex/skills/ralph-specum-refactor. 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 Ralph Specum Refactor?

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 Ralph Specum Refactor?

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

Is the Ralph Specum Refactor AI skill free?

Yes. It is published on GitHub by tzachbon 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

Ralph Specum Refactor

Contract

Action

Response Handoff

Bundled files

Frequently asked questions

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