Spec Workflow

Community

tzachbon

spec-workflow

This skill should be used when the user asks to "build a feature", "create a spec", "start spec-driven development", "run research phase", "generate requirements", "create design", "plan tasks", "implement spec", "check spec status", "triage a feature", "create an epic", "decompose a large feature", or needs guidance on spec-driven development workflow, phase ordering, or epic orchestration.

Overview

Publisher	tzachbon
Repository	`smart-ralph`
Skill name	`spec-workflow`
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 Spec Workflow 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/skills/spec-workflow
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/skills/spec-workflow

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/skills/spec-workflow .claude/skills/spec-workflow

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

Use it in TypingMind

Enable Spec 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 Spec 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 Spec 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.

Spec Workflow

Spec-driven development transforms feature requests into structured specs through sequential phases, then executes them task-by-task.

Decision Tree: Where to Start

Situation	Command
New feature, want guidance	`/ralph-specum:start <name> <goal>`
New feature, skip interviews	`/ralph-specum:start <name> <goal> --quick`
Large feature needing decomposition	`/ralph-specum:triage <goal>`
Resume existing spec	`/ralph-specum:start` (auto-detects)
Jump to specific phase	`/ralph-specum:<phase>`

Single Spec Flow


start/new -> research -> requirements -> design -> tasks -> implement
                         ^
                         optional prototype overlay, then return

Each phase produces a markdown artifact under the resolved <basePath>/. Normal mode pauses for approval between phases. Quick mode runs all phases then auto-starts execution.

Prototype is an optional overlay, not a main phase. The main phase remains research, requirements, design, tasks, or execution; live prototype work is stored in activePrototypes. Resolve the configured spec root and basePath before any overlay operation. Follow references/phase-transitions.md when suggesting, starting, resuming, cancelling, or consuming prototype evidence.

Phase Commands

Command	Agent	Output	Purpose
`/ralph-specum:research`	research-analyst	research.md	Explore feasibility, patterns, context
`/ralph-specum:requirements`	product-manager	requirements.md	User stories, acceptance criteria
`/ralph-specum:design`	architect-reviewer	design.md	Architecture, components, interfaces
`/ralph-specum:tasks`	task-planner	tasks.md	POC-first task breakdown
`/ralph-specum:implement`	spec-executor	commits	Autonomous task-by-task execution
`/ralph-specum:prototype`	prototype-builder	prototypes/<id>.md	Test one falsifiable design question in isolation

Normal mode may suggest prototype after research or requirements, and the user owns capture, verdict, handoff, and deletion decisions. Direct invocation is available from any main phase. Quick mode runs at most one agent-owned request after requirements, takes over the oldest design blocker when one exists, asks no decision questions, and always continues to design.

Epic Flow (Multi-Spec)

For features too large for a single spec, use epic triage to decompose into dependency-aware specs.


triage -> [spec-1, spec-2, spec-3...] -> implement each in order

Entry points:

/ralph-specum:triage <goal> -- create or resume an epic
/ralph-specum:start -- detects active epics, suggests next unblocked spec

File structure:


specs/
  _epics/<epic-name>/
    epic.md            # Triage output (vision, specs, dependency graph)
    research.md        # Exploration + validation research
    .epic-state.json   # Progress tracking across specs
    .progress.md       # Learnings and decisions

Management Commands

Command	Purpose
`/ralph-specum:status`	Show all specs and progress
`/ralph-specum:switch <name>`	Change active spec
`/ralph-specum:cancel`	Cancel active execution
`/ralph-specum:refactor`	Update spec files after execution

Common Workflows

Quick workflow

bash
/ralph-specum:start my-feature "Build X" --quick
# Runs all phases automatically, starts execution
# May run one unattended prototype request after requirements

Guided development

bash
/ralph-specum:start my-feature "Build X"
# Fact-first grilling at each phase
# Review and approve each artifact
/ralph-specum:implement

Large feature

bash
/ralph-specum:triage "Build entire auth system"
# Decomposes into: auth-core, auth-oauth, auth-rbac
/ralph-specum:start  # Picks next unblocked spec

References

references/phase-transitions.md -- Read for phase flow, prototype overlay entry and return, quick ownership, recovery, or phase skipping

Bundled files

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

references/phase-transitions.md7 KB

Frequently asked questions

What does the Spec Workflow AI skill do?

Why use Spec Workflow on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tzachbon/smart-ralph/tree/main/plugins/ralph-specum/skills/spec-workflow. 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 Spec 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 Spec Workflow?

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

Is the Spec Workflow 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

Spec Workflow

Decision Tree: Where to Start

Single Spec Flow

Phase Commands

Epic Flow (Multi-Spec)

Management Commands

Common Workflows

Quick workflow

Guided development

Large feature

References

Bundled files

Frequently asked questions

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