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Fable Workflow — copy-paste prompts

GPTClaudeDeepSeek··1,322 copies·updated 2026-07-14
fable-workflow-copy-paste-prompts.prompt
# Fable Workflow — copy-paste prompts

Paste these to any model. Works in English or Korean; capable models handle both.
Fill the `{…}` slots. These implement the loop in `SKILL.md`.

## Blind-spot pass (find unknown-unknowns)
> I'm about to work on **{task/module}** in this codebase, and I don't know it well yet.
> Do a **blind-spot pass**: read the relevant code (and {git diff / Slack / these docs:
> …} for context) and list the **unknown-unknowns** I should decide before we start —
> gotchas, hairy dead-ends, hidden coupling. Then tell me how to prompt you better.

New-domain variant:
> I know almost nothing about **{new field}**. Do a blind-spot pass and teach me the
> relevant unknowns — what would change my approach if I knew it?

## Interview me (fill known-unknowns)
> Before you build **{task}**, **interview me**. Ask one question at a time.
> **Prioritise questions that would change the architecture** or the core decisions.
> Context on me and where I'm at: {…}. Stop when the remaining questions are just details.

## Variants (surface unknown-knowns / taste calls)
> I have {no / weak} visual taste here. Make **{N=3–4} deliberately DIFFERENT** {designs /
> output formats / API shapes} for **{thing}** as {an HTML page / side-by-side samples} so
> I can react to them. Make them genuinely distinct, not three shades of one idea.

## Reference as map (skip writing the full spec)
> Here is {code / a mockup / an HTML page} that represents what I want: {paste or path}.
> It may be a different language/system. **Read it, understand the intent, then build
> {target}** in that spirit. Ask only if the intent is ambiguous.

## Log deviations (during build)
> While you build, keep a running **ASSUMPTIONS / IMPLEMENTATION NOTES** list: every time
> you hit something my spec didn't cover (an unknown), record it and the choice you made.
> Show the list with the result.

## Verify — make it real (before you call it done)
> Don't assert it works — **exercise it.** Code: run it, or write the smallest check that fails
> if the logic breaks, and show the output. Research/analysis: verify the key claim against a
> source. Design/doc: put it in the real context and show how it holds up.

## Correction loop (when verify fails)
> Don't retry blindly. Each attempt: state ONE hypothesis for *why* it failed, change only that,
> re-verify, and log hypothesis → change → result. Cap it at N tries. If the signal doesn't change
> across 2 iterations, stop and re-isolate — or tell me the unknown you hit. Don't loop forever.

## Quiz me (stay in the loop before merge)
> Before I open the PR, **quiz me** on what changed and why — the decisions I'd need to
> defend in review. Flag anything I get wrong or can't explain.

## One-shot / autonomous (can't ask back)
> You can't ask me questions on this run. So first write an **UNKNOWNS** list (the decision
> points my spec left open), pick a sensible default for each **and say why**, THEN implement.
> Surface the unknowns even though you're proceeding without me.

## Small / local models (≤ ~8B)

A weak model spends its limited capacity on the process and then botches the code — asking a
4B model to *derive* an implementation while also producing a full unknowns list makes the code
**worse**, not better (verified: gemma3:4b inverts the logic). Fix: cap the analysis and use the
**references-as-maps** move — have it *adapt a known-good reference* instead of deriving.

> You're building a small feature and CANNOT ask questions. Keep it short.
> STEP 1 — list only the **2–3 most important** open decisions, each with a one-line default.
> STEP 2 — implement by **ADAPTING the reference below** to those defaults. Keep its structure
> and algorithm; do NOT invent a new approach.
>
> REFERENCE (a known-good implementation of the pattern you want — adapt, don't rewrite):
> ```
> {paste a correct example/skeleton of the target pattern}
> ```
>
> TASK: {your task + spec}

No reference handy? Prefer a stronger local model — per the benchmark, a reasoning model
(qwen3.6) handled the full method fine (82→87), while gemma3:4b needed this variant.

fill the variables

This prompt has 15 variables. Pro fills them into a ready-to-paste prompt for you — no manual find-and-replace.

{…}{task/module}{git diff / Slack / these docs: > …}{new field}{task}{no / weak}{N=3–4}{designs / > output formats / API shapes}{thing}{an HTML page / side-by-side samples}{code / a mockup / an HTML page}{paste or path}{target}{paste a correct example/skeleton of the target pattern}{your task + spec}
Unlock with Pro →

when to use it

Community prompt sourced from the open-source GitHub repo joey114132/fable-workflow-skill (MIT). A "Fable Workflow — copy-paste prompts" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.

tags

codingcommunitydeveloper

source

joey114132/fable-workflow-skill · MIT