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List Features

Community
krishnakanthb13
list_features

Scans the codebase to generate a comprehensive, prompt-based feature list in 'features_listed.md' for recreating the app in any language.

Overview

Publisherkrishnakanthb13
Repositoryantigravity_global_skills
Skill namelist_features
Stars
66
Forks
11
Bundled files
Instructions only
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 krishnakanthb13 on GitHub. Read the source before you install it.

Installation

Install the List Features 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/krishnakanthb13/antigravity_global_skills/tree/main/list_features
  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/krishnakanthb13/antigravity_global_skills.git /tmp/antigravity_global_skills
mkdir -p .claude/skills
cp -r /tmp/antigravity_global_skills/list_features .claude/skills/list_features
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable List Features 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 List Features 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 List Features 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.

List Features (Recreation Spec)

Use this skill to extract a complete, technically precise blueprint of the application, formatted as a series of prompts that could be used to rebuild the app from scratch.

Inputs

  • Project Scope: The root directory of the application to analyze.
  • Output File: features_listed.md (default).

Tooling Strategy

  • Use list_dir to map the project structure.
  • Use view_file to inspect README.md, CODE_DOCUMENTATION.md (if available), and key source files (entry points, controllers, UI components).
  • Use write_to_file to generate the final Markdown report.

Workflow

1. Analysis (Deep Scan)

  • Objective: Understand exactly what the app does, not just how it's written.
  • Sources:
    • Documentation (README.md, DESIGN_PHILOSOPHY.md).
    • Configuration (package.json, requirements.txt) to identify tech stack implications.
    • Source Code: Look for routes, UI components, state management, and database schemas.

2. Feature Extration & Prompt Generation

For every identified feature, convert it into a Technical Prompt.

  • Format: "Implement [Feature Name] using [Input/Constraint]. The system must [Action] when [Trigger]."
  • Precision: Use standard technical jargon (e.g., "JWT Authentication", "Responsive Grid Layout", "RESTful Endpoint", "WebSocket Stream").
  • Completeness: If a button exists, the feature is "Clickable Button that triggers X". If a background task runs, the feature is "Background Cron Job for X".

3. Report Structuring (features_listed.md)

Create a file that looks like a specification document for an AI or Developer:

Structure:

  1. Core Architecture: High-level stack agnostic requirements (e.g., "Client-Server Architecture").
  2. User Interface (UI): Detailed prompts for every page/component (e.g., "Create a dashboard with glassmorphism...").
  3. Business Logic & Functional Requirements: (e.g., "Calculate tax based on...").
  4. Data Persistence: (e.g., "Schema must support...").
  5. API & Integration: (e.g., "Expose GET /api/v1/users...").

4. Verification

  • The "Rebuild Test": Ask yourself: "If I gave this file to a stranger, could they build the exact same app without seeing the code?"
  • Ensure no hidden features (middleware, schedulers) are missed.

5. Final Output

  • Save the file to features_listed.md in the project root.

Advanced Feature Extraction (Recreation Standards)

When extracting features, ensure you also capture the underlying mechanics:

  • Domain Modeling: Extract the core data entities and their relationships (e.g., "User has many Orders, Order has many Items").
  • Third-Party Dependencies: Explicitly call out if a feature relies on an external API or specific SDK (e.g., "Payment processing via Stripe API").
  • State Management: Note how global state or complex UI states are handled, as this drastically changes how the app is rebuilt.

Frequently asked questions

What does the List Features AI skill do?

Scans the codebase to generate a comprehensive, prompt-based feature list in 'features_listed.md' for recreating the app in any language.

Why use List Features on TypingMind?

Because you install it once and use it with any model. List Features 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 List Features in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/krishnakanthb13/antigravity_global_skills/tree/main/list_features. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use List Features?

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 List Features?

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

Is the List Features AI skill free?

It is published on GitHub by krishnakanthb13. Check the repository for licensing terms. 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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