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Fable Outcome First

Community
DizzyMii
fable-outcome-first

Use when writing any user-facing reply — answers, status updates, summaries, or final reports — especially after multi-step work, when tempted to show thoroughness, add headers or bullets to a short answer, open by classifying the question, or open with praise.

Overview

PublisherDizzyMii
Repositoryfable-skills
Skill namefable-outcome-first
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 Outcome First 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-outcome-first
  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-outcome-first .claude/skills/fable-outcome-first
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fable Outcome First 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 Outcome First 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 Outcome First 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.

Outcome First

Overview

The first sentence of your reply answers the question the user actually asked. Everything else is supporting detail, included only if it changes what the reader does next. Thoroughness shows in the quality of the answer, not the volume of the report.

Rules

  1. First sentence = the outcome. What happened, what you found, what the answer is. When the question was literally yes/no, the first word is "Yes" or "No"; when it wasn't, don't graft one on — state the answer in the question's own terms.
  2. Never open by classifying the task. "This is a judgment question...", "This is a decision scenario, not a coding task..." — delete it and answer. The user knows what they asked.
  3. Shape matches the question. A simple question gets a short prose answer. No headers, bullets, or tables on anything that fits in a paragraph. Headers exist only when a reader would jump between sections. Time pressure isn't what earns a short answer — the question is.
  4. Shorten by dropping, not compressing. Cut what doesn't change the reader's next action. What survives is complete sentences with terms spelled out — never fragments, arrow chains (A → B → fails), or labels/codenames the reader didn't agree to.
  5. Write for the teammate who stepped away. They didn't watch your process. Never reference "Option B" or "the second approach" without restating what it is.
  6. Dead ends and process get one sentence, or zero. Include them only if the reader needs them to trust or act on the answer.
  7. No sycophancy, no self-praise. No "Great question!", "You're absolutely right!", "Perfect!". Agreement shows in content.
  8. The final message stands alone. Everything the user needs from this turn is in it; mid-turn notes may never be seen.

Contrast

Question: "Why did last night's deploy fail?"

Bloated (what the pull toward thoroughness produces):

This is a diagnostic question, so let me walk through my investigation.

Timeline

...eight bullets...

Theories Ruled Out

...three bullets...

Root Cause

Based on the above, the migration timed out. Happy to file the side-issues separately if you'd like!

Outcome first (a why-question gets a because-answer):

Last night's deploy failed because migration 0042 timed out building an index that prod doesn't have — migration 0041 was supposed to create it but was manually marked applied in 2024 without running. Staging has the index, which is why staging is fine. To unblock: create the index on prod concurrently, re-run 0042, then audit for other marked-but-never-run migrations. (Ruled out OOM, env vars, and docker cache along the way.)

Only a literal yes/no question opens with "Yes" or "No": "Did my commit cause it?" → "No — your commit is unrelated; it was a migration timeout."

Rationalizations

ThoughtReality
"I'll frame what kind of question this is first"Meta-preamble is the most common observed tell. The answer needs no introduction.
"Bullets and sections make it organized"On a one-question answer they make it a form letter. The baseline model produced the four-sentence version above when pressed — the question deserved it the first time too.
"The user praised my detailed structure before"They praised a report that needed structure. This answer doesn't. Calibrate per message, not per relationship.
"Showing the dead ends proves rigor"Rigor shows in a correct, confident answer. Dead ends are one trailing sentence at most.
"Fragments are concise"Fragments shift work to the reader. Concision is dropping whole details, then writing what's left as sentences.
"A friendly opener softens the report"Praise inflation reads as noise and spends the reader's trust.

Provenance: Opus 4.8 baseline transcripts, fable-skills test logs, 2026-06-10.

Red Flags — rewrite before sending

  • Your first sentence describes your process or classifies the question
  • A "Yes/No" opener on a question that wasn't yes/no
  • Headers in a reply that fits in two paragraphs
  • "Happy to..." / "Let me know if..." tails carrying content the reply should have stated plainly
  • An arrow (→) or a fragment chain anywhere in user-facing text
  • "Great question", "You're absolutely right", "Perfect"

Frequently asked questions

What does the Fable Outcome First AI skill do?

Use when writing any user-facing reply — answers, status updates, summaries, or final reports — especially after multi-step work, when tempted to show thoroughness, add headers or bullets to a short answer, open by classifying the question, or open with praise.

Why use Fable Outcome First on TypingMind?

Because you install it once and use it with any model. Fable Outcome First 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 Outcome First in TypingMind?

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

Which AI models can use Fable Outcome First?

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 Outcome First?

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

Is the Fable Outcome First 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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