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Ralph Tui Create Json

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subsy
ralph-tui-create-json

Convert PRDs to prd.json format for ralph-tui execution. Creates JSON task files with user stories, acceptance criteria, and dependencies. Triggers on: create prd.json, convert to json, ralph json, create json tasks.

Overview

Publishersubsy
Repositoryralph-tui
Skill nameralph-tui-create-json
Stars
2.4K
Forks
238
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Ralph Tui Create Json 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/subsy/ralph-tui.git /tmp/ralph-tui
mkdir -p .claude/skills
cp -r /tmp/ralph-tui/skills/ralph-tui-create-json .claude/skills/ralph-tui-create-json
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ralph Tui Create Json 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 Tui Create Json 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 Tui Create Json 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 TUI - Create JSON Tasks

Converts PRDs to prd.json format for ralph-tui autonomous execution.

Note: This skill is bundled with ralph-tui's JSON tracker plugin. Future tracker plugins (Linear, GitHub Issues, etc.) will bundle their own task creation skills.

⚠️ CRITICAL: The output MUST be a FLAT JSON object with "name" and "userStories" at the ROOT level. DO NOT wrap content in a "prd" object or use "tasks" array. See "Schema Anti-Patterns" section below.


The Job

Take a PRD (markdown file or text) and create a prd.json file:

  1. Extract Quality Gates from the PRD's "Quality Gates" section
  2. Parse user stories from the PRD
  3. Append quality gates to each story's acceptance criteria
  4. Set up dependencies between stories
  5. Output ready for ralph-tui run --prd <path>

Step 1: Extract Quality Gates

Look for the "Quality Gates" section in the PRD:

markdown
## Quality Gates

These commands must pass for every user story:
- `pnpm typecheck` - Type checking
- `pnpm lint` - Linting

For UI stories, also include:
- Verify in browser using dev-browser skill

Extract:

  • Universal gates: Commands that apply to ALL stories (e.g., pnpm typecheck)
  • UI gates: Commands that apply only to UI stories (e.g., browser verification)

If no Quality Gates section exists: Ask the user what commands should pass, or use a sensible default like npm run typecheck.


Output Format

The JSON file MUST be a FLAT object at the root level:

json
{
  "name": "[Project name from PRD or directory]",
  "branchName": "ralph/[feature-name-kebab-case]",
  "description": "[Feature description from PRD]",
  "userStories": [
    {
      "id": "US-001",
      "title": "[Story title]",
      "description": "As a [user], I want [feature] so that [benefit]",
      "acceptanceCriteria": [
        "Criterion 1 from PRD",
        "Criterion 2 from PRD",
        "pnpm typecheck passes",
        "pnpm lint passes"
      ],
      "priority": 1,
      "passes": false,
      "notes": "",
      "dependsOn": []
    },
    {
      "id": "US-002",
      "title": "[UI Story that depends on US-001]",
      "description": "...",
      "acceptanceCriteria": [
        "...",
        "pnpm typecheck passes",
        "pnpm lint passes",
        "Verify in browser using dev-browser skill"
      ],
      "priority": 2,
      "passes": false,
      "notes": "",
      "dependsOn": ["US-001"]
    }
  ]
}

CRITICAL: Schema Anti-Patterns (DO NOT USE)

The following patterns are INVALID and will cause validation errors:

❌ WRONG: Wrapper object

json
{
  "prd": {
    "name": "...",
    "userStories": [...]
  }
}

This wraps everything in a "prd" object. DO NOT DO THIS. The "name" and "userStories" fields must be at the ROOT level.

❌ WRONG: Using "tasks" instead of "userStories"

json
{
  "name": "...",
  "tasks": [...]
}

The array is called "userStories", not "tasks".

❌ WRONG: Complex nested structures

json
{
  "metadata": {...},
  "overview": {...},
  "migration_strategy": {
    "phases": [...]
  }
}

Even if the PRD describes phases/milestones/sprints, you MUST flatten these into a single "userStories" array.

❌ WRONG: Using "status" instead of "passes"

json
{
  "userStories": [{
    "id": "US-001",
    "status": "open"  // WRONG!
  }]
}

Use "passes": false for incomplete stories, "passes": true for completed.

✅ CORRECT: Flat structure at root

json
{
  "name": "Android Kotlin Migration",
  "branchName": "ralph/kotlin-migration",
  "userStories": [
    {"id": "US-001", "title": "Create Scraper interface", "passes": false, "dependsOn": []},
    {"id": "US-002", "title": "Implement WeebCentralScraper", "passes": false, "dependsOn": ["US-001"]}
  ]
}

Story Size: The #1 Rule

Each story must be completable in ONE ralph-tui iteration (~one agent context window).

Ralph-tui spawns a fresh agent instance per iteration with no memory of previous work. If a story is too big, the agent runs out of context before finishing.

Right-sized stories:

  • Add a database column + migration
  • Add a UI component to an existing page
  • Update a server action with new logic
  • Add a filter dropdown to a list

Too big (split these):

  • "Build the entire dashboard" → Split into: schema, queries, UI components, filters
  • "Add authentication" → Split into: schema, middleware, login UI, session handling
  • "Refactor the API" → Split into one story per endpoint or pattern

Rule of thumb: If you can't describe the change in 2-3 sentences, it's too big.


Dependencies with dependsOn

Use the dependsOn array to specify which stories must complete first:

json
{
  "id": "US-002",
  "title": "Create API endpoints",
  "dependsOn": ["US-001"],  // Won't be selected until US-001 passes
  ...
}

Ralph-tui will:

  • Show US-002 as "blocked" until US-001 completes
  • Never select US-002 for execution while US-001 is open
  • Include "Prerequisites: US-001" in the prompt when working on US-002

Correct dependency order:

  1. Schema/database changes (no dependencies)
  2. Backend logic (depends on schema)
  3. UI components (depends on backend)
  4. Integration/polish (depends on UI)

Acceptance Criteria: Quality Gates + Story-Specific

Each story's acceptance criteria should include:

  1. Story-specific criteria from the PRD (what this story accomplishes)
  2. Quality gates from the PRD's Quality Gates section (appended at the end)

Good criteria (verifiable):

  • "Add status column to tasks table with default 'open'"
  • "Filter dropdown has options: All, Open, Closed"
  • "Clicking delete shows confirmation dialog"

Bad criteria (vague):

  • ❌ "Works correctly"
  • ❌ "User can do X easily"
  • ❌ "Good UX"
  • ❌ "Handles edge cases"

Conversion Rules

  1. Extract Quality Gates from PRD first
  2. Each user story → one JSON entry
  3. IDs: Sequential (US-001, US-002, etc.)
  4. Priority: Based on dependency order (1 = highest)
  5. dependsOn: Array of story IDs this story requires
  6. All stories: passes: false and empty notes
  7. branchName: Derive from feature name, kebab-case, prefixed with ralph/
  8. Acceptance criteria: Story criteria + quality gates appended
  9. UI stories: Also append UI-specific gates (browser verification)

Output Location

Default: ./tasks/prd.json (alongside the PRD markdown files)

This keeps all PRD-related files together in the tasks/ directory.

Or specify a different path - ralph-tui will use it with:

bash
ralph-tui run --prd ./path/to/prd.json

Example

Input PRD:

markdown
# PRD: Task Priority System

Add priority levels to tasks.

## Quality Gates

These commands must pass for every user story:
- `pnpm typecheck` - Type checking
- `pnpm lint` - Linting

For UI stories, also include:
- Verify in browser using dev-browser skill

## User Stories

### US-001: Add priority field to database
**Description:** As a developer, I need to store task priority.

**Acceptance Criteria:**
- [ ] Add priority column: 1-4 (default 2)
- [ ] Migration runs successfully

### US-002: Display priority badge on task cards
**Description:** As a user, I want to see task priority at a glance.

**Acceptance Criteria:**
- [ ] Badge shows P1/P2/P3/P4 with colors
- [ ] Badge visible without hovering

### US-003: Add priority filter dropdown
**Description:** As a user, I want to filter tasks by priority.

**Acceptance Criteria:**
- [ ] Filter dropdown: All, P1, P2, P3, P4
- [ ] Filter persists in URL

Output prd.json:

json
{
  "name": "Task Priority System",
  "branchName": "ralph/task-priority",
  "description": "Add priority levels to tasks",
  "userStories": [
    {
      "id": "US-001",
      "title": "Add priority field to database",
      "description": "As a developer, I need to store task priority.",
      "acceptanceCriteria": [
        "Add priority column: 1-4 (default 2)",
        "Migration runs successfully",
        "pnpm typecheck passes",
        "pnpm lint passes"
      ],
      "priority": 1,
      "passes": false,
      "notes": "",
      "dependsOn": []
    },
    {
      "id": "US-002",
      "title": "Display priority badge on task cards",
      "description": "As a user, I want to see task priority at a glance.",
      "acceptanceCriteria": [
        "Badge shows P1/P2/P3/P4 with colors",
        "Badge visible without hovering",
        "pnpm typecheck passes",
        "pnpm lint passes",
        "Verify in browser using dev-browser skill"
      ],
      "priority": 2,
      "passes": false,
      "notes": "",
      "dependsOn": ["US-001"]
    },
    {
      "id": "US-003",
      "title": "Add priority filter dropdown",
      "description": "As a user, I want to filter tasks by priority.",
      "acceptanceCriteria": [
        "Filter dropdown: All, P1, P2, P3, P4",
        "Filter persists in URL",
        "pnpm typecheck passes",
        "pnpm lint passes",
        "Verify in browser using dev-browser skill"
      ],
      "priority": 3,
      "passes": false,
      "notes": "",
      "dependsOn": ["US-002"]
    }
  ]
}

Running with ralph-tui

After creating prd.json:

bash
ralph-tui run --prd ./tasks/prd.json

Ralph-tui will:

  1. Load stories from prd.json
  2. Select the highest-priority story with passes: false and no blocking dependencies
  3. Generate a prompt with story details + acceptance criteria
  4. Run the agent to implement the story
  5. Mark passes: true on completion
  6. Repeat until all stories pass

Checklist Before Saving

  • Extracted Quality Gates from PRD (or asked user if missing)
  • Each story completable in one iteration
  • Stories ordered by dependency (schema → backend → UI)
  • dependsOn correctly set for each story
  • Quality gates appended to every story's acceptance criteria
  • UI stories have browser verification (if specified in Quality Gates)
  • Acceptance criteria are verifiable (not vague)
  • No circular dependencies

Frequently asked questions

What does the Ralph Tui Create Json AI skill do?

Convert PRDs to prd.json format for ralph-tui execution. Creates JSON task files with user stories, acceptance criteria, and dependencies. Triggers on: create prd.json, convert to json, ralph json, create json tasks.

Why use Ralph Tui Create Json on TypingMind?

Because you install it once and use it with any model. Ralph Tui Create Json 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 Tui Create Json in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/subsy/ralph-tui/tree/main/skills/ralph-tui-create-json. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ralph Tui Create Json?

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 Tui Create Json?

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

Is the Ralph Tui Create Json AI skill free?

Yes. It is published on GitHub by subsy 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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