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Fable Native Code

Community
DizzyMii
fable-native-code

Use when writing or editing code in an existing codebase — before adding comments, docstrings, try/catch blocks, validation, logging, or TODOs the surrounding file doesn't have, and before explaining your style choices in the reply.

Overview

PublisherDizzyMii
Repositoryfable-skills
Skill namefable-native-code
Stars
56
Forks
11
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 DizzyMii on GitHub. Read the source before you install it.

Installation

Install the Fable Native Code 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/DizzyMii/fable-skills/tree/main/skills/fable-native-code
  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/DizzyMii/fable-skills.git /tmp/fable-skills
mkdir -p .claude/skills
cp -r /tmp/fable-skills/skills/fable-native-code .claude/skills/fable-native-code
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fable Native Code 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 Fable Native Code 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 Fable Native Code 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.

Native Code

Overview

Your diff should read like the file's longtime owner wrote it. The file has a style — naming, error handling, comment density, formatting. Write in it. Your personal preferences are not improvements; they're an accent.

Rules

  1. Match the file: naming, error-handling idiom, comment density, formatting, import organization. If the file has one comment per 200 lines, your addition almost certainly has zero.
  2. Comments state only constraints the code cannot show — invariants, gotchas, why-not-the-obvious-way. Never what the next line does, never narration of your change ("now correctly handles X"), never justification aimed at a reviewer. Test: after the PR merges, is this comment information or noise?
  3. No defensive bloat: no try/catch around code that works, no validating invariants the types or callers already guarantee, no logging, config, or flags nobody asked for. If the contract is worth enforcing, that's a test or a boundary assertion — its own change.
  4. Don't narrate your restraint. The urge to explain what you didn't add ("note: I deliberately left out the doc comment because…") is the same urge that adds it — displaced into the reply. The justification a senior dev never writes in code, they also never write in chat. Deliver the code; mention style only if the user asks.
  5. Clean exit: no debug prints, no commented-out code, no TODO crumbs you created.
  6. Names come from the codebase's existing vocabulary. Don't coin a second name for an existing concept.

Contrast

Task: add clampWindow to a terse Go file whose only comment in 200 lines marks a sorting invariant; callers guarantee max >= 0.

Foreign (your habits, not the file's):

go
// clampWindow clamps start and end into the valid range [0, max] and
// normalizes inverted windows. Returns (start, start) when end < start.
func clampWindow(start, end, max int) (int, int) {
    if max < 0 {
        return 0, 0 // defensive: should never happen
    }
    ...
}

Native (what the file's owner would write):

go
func clampWindow(start, end, max int) (int, int) {
    if start < 0 {
        start = 0
    }
    if start > max {
        start = max
    }
    if end < 0 {
        end = 0
    }
    if end > max {
        end = max
    }
    if end < start {
        return start, start
    }
    return start, end
}

No header comment (the signature says it), no max < 0 guard (the callers guarantee it, like mergeWindows trusts its sorted-input invariant) — and no paragraph in the reply explaining either omission.

Rationalizations

ThoughtReality
"A doc comment helps the next reader"The next reader has the signature and twelve obvious lines. The file's owner trusted them; trust them too.
"Extra validation can't hurt"A guard for an impossible state is dead code that suggests the state is possible. Swallowed errors are the most expensive bugs to find.
"My last reviewer praised my documentation habits"In a codebase whose style wants documentation. This file's style is the spec now.
"I'll explain in chat what I left out of the code"Observed verbatim in baseline: a multi-paragraph "note on what I deliberately left out" after "output only the code." Restraint that announces itself isn't restraint.
"I'll leave a TODO for the edge case"Handle it, or surface it in your report. TODOs are where edge cases go to be forgotten.

Provenance: baseline Opus 4.8 wrote the native version above, then narrated its restraint anyway (rule 4 exists because of it). fable-skills test logs, 2026-06-10.

Red Flags — delete before committing

  • A comment that describes the line below it
  • "deliberately", "note that I", "for safety" — in code or in your reply
  • try/catch whose catch block only logs or re-raises
  • A guard for a state the caller contract excludes
  • Your addition is the only part of the file with comments

Frequently asked questions

What does the Fable Native Code AI skill do?

Use when writing or editing code in an existing codebase — before adding comments, docstrings, try/catch blocks, validation, logging, or TODOs the surrounding file doesn't have, and before explaining your style choices in the reply.

Why use Fable Native Code on TypingMind?

Because you install it once and use it with any model. Fable Native Code 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 Fable Native Code in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/DizzyMii/fable-skills/tree/main/skills/fable-native-code. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Fable Native Code?

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 Fable Native Code?

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

Is the Fable Native Code AI skill free?

Yes. It is published on GitHub by DizzyMii 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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