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Ralph Specum Design

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tzachbon
ralph-specum-design

This skill should be used only when the user explicitly asks to use `$ralph-specum-design`, or explicitly asks Ralph Specum in Codex to run the design phase.

Overview

Publishertzachbon
Repositorysmart-ralph
Skill nameralph-specum-design
Stars
559
Forks
50
Bundled files
1
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.

  • 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 Design 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/tzachbon/smart-ralph/tree/main/plugins/ralph-specum-codex/skills/ralph-specum-design
  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/tzachbon/smart-ralph.git /tmp/smart-ralph
mkdir -p .claude/skills
cp -r /tmp/smart-ralph/plugins/ralph-specum-codex/skills/ralph-specum-design .claude/skills/ralph-specum-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ralph Specum Design 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 Design 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 Design 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 Design

You are a coordinator, not an architect -- delegate ALL work to an architect-reviewer sub-agent.

Derive RALPH_CODEX_PLUGIN_ROOT from this loaded skill by resolving two parent directories from the SKILL.md directory. Never derive it from the project working directory.

Contract

  • Resolve the active spec by explicit path, exact name, or .current-spec
  • Require requirements.md
  • Merge state fields only
  • Keep the Ralph disk contract unchanged

Action

  1. Resolve the active spec. If none exists, stop.
  2. Require requirements.md. Read research.md when present, .progress.md, and current state.
  3. Run phase_gate.py mode through "$RALPH_CODEX_PLUGIN_ROOT/scripts/phase_gate.py" with STATE and exact --quick, exact --interactive, or no flag. Reject both, -q, variants, and natural-language substitutes.
  4. In interactive mode, require artifact approval for the current requirements.md before starting design. Exact quick mode continues with the validated artifact.
  5. Run prototype record selection with the resolved basePath before generation:
    bash
    python3 "$RALPH_CODEX_PLUGIN_ROOT/scripts/prototype_records.py" select-downstream --base-path "$BASE_PATH" --state "$BASE_PATH/.ralph-state.json"
  6. Include only affected, valid, gateApproved: true, non-superseded records returned by the selector. Exclude malformed, superseded, skipped, failed, inconclusive, cancelled, and normal-mode excluded records.
  7. Stop before generation when selection reports an activePrototypes blocker for design. Name the active ID and route resume through $ralph-specum-prototype.
  8. Stop when selection reports stale requirements, research, design, or task indexes that affect design. Route to the earliest stale phase. Allow proven unrelated work only when the selector reports no dependency on the active prototype, stale artifact, stale task index, or approved transfer path.
  9. Clear any prior approval gate by merging awaitingApproval: false before generation.
  10. When research.md exists, require skill discovery pass 2 against the goal plus final research. When it is absent, require pass 1 against the goal alone. Run the applicable pass when the state lacks its revision. Select explicitly named skills and record harness-shadowed duplicates.
  11. Load "$RALPH_CODEX_PLUGIN_ROOT/skills/interview-framework-codex/SKILL.md", its required algorithm and domain-modeling references, and all selected domain contracts in both interactive and quick mode. In interactive mode, use its focused brainstorming method for material architecture choices, stable interfaces, compatibility or migration decisions, and operational risk. Inspect repository facts and existing conventions instead of asking.
  12. In interactive mode, require explicit approve and delegate; in exact quick mode, record bypassed_quick. In both modes, run phase_gate.py check-delegation with the current loaded-manifest identity before creating the child. Apply the shared hard-transition invariant before design writer dispatch. A failed check-delegation in either mode ends this invocation before phase transition, child dispatch, or target-artifact write; after a normal-mode failure, the next explicit invocation creates a fresh manifest/interview identity and does not create an alternate quick bypass. After an exact --quick delegation failure, the next explicit invocation reruns discovery, records a fresh phaseSkillLoad and interview identity, and does not reuse a terminal bypassed_quick interview or its discovery revision. Only a matching in-progress collecting or awaiting_confirmation interview is resumable.
  13. Delegate design generation to an architect-reviewer sub-agent. Pass the absolute helper path, state path, identity tuple, unique teammate dispatch identity, verbatim manifest, requirements, research, selected prototype evidence, the clean blocker/stale-gate result, and interview context. The child reloads and records the manifest, passes check-agent-write with that unique identity, and writes design.md. Do NOT write design.md yourself.
  14. Read the sub-agent's output and validate it exists.
  15. Merge state with phase: "design" and awaitingApproval: true (or false when exact --quick is active).
  16. Update .progress.md with design decisions, open risks, integration contracts, skill discovery, and next step.
  17. If spec commits are enabled, commit only the spec artifacts.

Stop Behavior

  • Without --quick: STOP HERE. Display the walkthrough summary and approval prompt. Do NOT continue to tasks. Wait for the user to explicitly approve and request the next phase.
  • With exact --quick: Record the quick bypass and continue directly into tasks.

Output Shape

The result should cover architecture, interfaces, data flow, file changes, technical decisions, error handling, and test strategy.

Response Handoff

  • After writing design.md, name design.md and summarize the design briefly.
  • When normalized quickMode is false, end with exactly one explicit choice prompt:
    • approve current artifact
    • request changes
    • continue to tasks
  • Treat continue to tasks as approval of design.md.
  • With exact --quick, do not show this prompt; continue directly to tasks after the gates succeed.
  • During artifact review, apply the changes immediately delegates already-recorded feedback through a new unique dispatch, redisplays the artifact, and stays at this approval gate. Ask one focused change question only when no feedback is pending. Control-only continue, proceed, and go ahead approve nothing.

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 Ralph Specum Design AI skill do?

This skill should be used only when the user explicitly asks to use `$ralph-specum-design`, or explicitly asks Ralph Specum in Codex to run the design phase.

Why use Ralph Specum Design on TypingMind?

Because you install it once and use it with any model. Ralph Specum Design 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 Design 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-design. 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 Design?

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 Design?

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

Is the Ralph Specum Design 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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