Feature List Json logo

Feature List Json

Community
Archive228
feature-list-json

Enumerate every end-to-end feature as strict JSON entries with passes:false, editable-passes-only discipline, and priority order. The ledger fresh-context sessions read to know what's done, what's next, and what they're forbidden to touch.

Overview

PublisherArchive228
Repositoryloopkit
Skill namefeature-list-json
Stars
755
Forks
124
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 Archive228 on GitHub. Read the source before you install it.

Installation

Install the Feature List 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.
    https://github.com/Archive228/loopkit/tree/main/skills/feature-list-json
  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/Archive228/loopkit.git /tmp/loopkit
mkdir -p .claude/skills
cp -r /tmp/loopkit/skills/feature-list-json .claude/skills/feature-list-json
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feature List 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 Feature List 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 Feature List 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.

feature_list.json

The ledger of every feature the product will eventually have. Fresh-context sessions read it to pick work; they flip exactly one boolean when done. JSON, not Markdown — the syntactic strictness is load-bearing. Prose gets edited freely; data gets edited carefully.

Format per entry:

json
{
  "category": "functional",
  "description": "New chat button creates a fresh conversation",
  "steps": [
    "Navigate to main interface",
    "Click the 'New Chat' button",
    "Verify a new conversation is created",
    "Check that chat area shows welcome state",
    "Verify conversation appears in sidebar"
  ],
  "passes": false
}

Categories: functional, ux, data, infra. Order the array in implementation order — the top is the next thing to build.

When to apply

  • Initializer agent at scaffold time: produce the full list, every entry passes: false. Aim for breadth — 200 well-scoped entries beats 30 vague ones.
  • Coding agent at end of session: after end-to-end verification, flip exactly one passes from false to true.
  • Any session at start: jq '[.[] | select(.passes==false)] | length' to see remaining work; pick the topmost unblocked entry.

Procedure — initializer

  1. Enumerate every user-observable behavior the spec implies. Login, list rendering, empty states, error states, keyboard shortcuts, mobile layout — all of it.
  2. Write each as one entry. description is one sentence, steps is a user's actual action sequence (not implementation notes).
  3. Order the array so an agent walking top-to-bottom builds prerequisites before dependents.
  4. Every passes starts false. No exceptions, not even for the smoke test.
  5. Validate: jq '. | length' returns your count; jq '[.[] | select(.passes==true)] | length' returns 0.

Procedure — coding agent

  1. Read the file. Do not edit yet.
  2. Pick the topmost entry with passes: false and satisfied prerequisites. If the top is blocked, drop to the deepest unblocked entry.
  3. Implement. Test. Verify end-to-end via the runtime path (browser automation, HTTP, CLI) — not unit tests alone. See [[broken-window-check]] for what E2E means.
  4. Only after E2E green: flip that single entry's passes to true.
  5. Diff the file. The diff must be exactly one false → true. Nothing else.

Anti-patterns

  • Editing description, steps, or category — it is unacceptable to remove or edit these fields because it lets missing functionality slip past future sessions. The ledger is append-only in every field except passes.
  • Flipping passes: true on unit-test evidence — unit tests pass while routes are misrouted, CORS is broken, or the button is unwired. Only end-to-end evidence flips the bit. See [[verification-before-completion]].
  • Flipping multiple entries in one session — the single-feature-per-session rule (see [[one-feature-per-session]]) exists because packed sessions ship everything half-done. One flip per session.
  • Adding new entries mid-project without spec change — if scope grew, note it in [[shift-notes]] and flag for a re-scope, don't quietly extend the ledger.
  • Deleting "obsolete" entries — if a feature is no longer needed, leave it and mark it passes: true with a note, or negotiate removal explicitly. Silent deletion breaks priority counting.
  • Markdown or YAML instead of JSON — measured in shift-work agent runs, JSON cuts spurious field edits ~7x vs. Markdown and premature-pass marking ~2x. The strictness does the work.

Audit check

At session end, before committing:

bash
git diff feature_list.json | grep -E '^[-+]' | grep -v 'passes'

If this prints anything other than the file header, you edited a forbidden field. Revert those hunks. Only "passes": false ↔ "passes": true lines are allowed to change.

When NOT to apply

  • Projects under ~20 features — the overhead of writing the list exceeds the benefit; a flat TODO in [[shift-notes]] is enough.
  • Solo one-shot sessions with no handoff — the ledger's whole purpose is cross-session discipline.

Related

  • [[shift-notes]] — the prose companion; feature_list.json holds state, shift-notes holds context.
  • [[broken-window-check]] — what "end-to-end verified" means before you flip a bit.
  • [[one-feature-per-session]] — the rule that limits you to one flip per session.
  • [[verification-before-completion]] — the general form of "no bit-flip without runtime evidence".

Frequently asked questions

What does the Feature List Json AI skill do?

Enumerate every end-to-end feature as strict JSON entries with passes:false, editable-passes-only discipline, and priority order. The ledger fresh-context sessions read to know what's done, what's next, and what they're forbidden to touch.

Why use Feature List Json on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Archive228/loopkit/tree/main/skills/feature-list-json. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Feature List 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 Feature List Json?

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

Is the Feature List Json AI skill free?

Yes. It is published on GitHub by Archive228 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇