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Goudi

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hylarucoder
goudi

Pressure-tests an ambitious proposal and returns a landing judgment, one minimum viable proof, explicit cuts, success/failure signals, and a stop rule. Use when a direction has more vision than executable grounding or the user asks how to land it, reduce first-step scope, price risk, or define rollback(落地、别太飘、最小可行、止损). Use geju when the goal is to open the frame rather than ground an existing direction.

Overview

Publisherhylarucoder
Repositoryhai-stack
Skill namegoudi
Stars
284
Forks
15
Bundled files
4
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hylarucoder on GitHub. Read the source before you install it.

Installation

Install the Goudi 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.
  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/hylarucoder/hai-stack.git /tmp/hai-stack
mkdir -p .claude/skills
cp -r /tmp/hai-stack/skills/goudi .claude/skills/goudi
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Goudi 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 Goudi 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 Goudi 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.

Goudi

For Chinese readers, see SKILL.zh_CN.md. The English SKILL.md is the execution source of truth.

Overview

Use this skill when a discussion has too much ambition and too little executable grounding. goudi is the counterweight to geju: geju opens the frame; goudi forces the move to land.

This skill is not about being timid, conservative, or anti-refactor. It is about making the chosen direction survivable, verifiable, reversible where possible, and useful in the next concrete step.

Core Principle

先把路踩实,再谈大胜利。

Big ideas are allowed. Sweeping redesigns are allowed. Strong architecture opinions are allowed. But a useful proposal must answer:

  • What is the smallest move that proves this direction?
  • What evidence says the move is working?
  • What real constraint can break it?
  • What should be deliberately cut from the first attempt?
  • Where is the stop rule if the thesis is wrong?

If the answer cannot produce a concrete first move, it is not a plan yet. It is only a mood.

goudi and geju are a designed pair:

  • geju: "What is the clean target if we stop being scared?"
  • goudi: "What is the first proof that this target can survive contact with reality?"

Do not let goudi erase the bold target. Compress the first step, not the ambition.

Workflow

  1. Restate the bold direction in one sentence. Do not flatten the ambition. Name where it came from — geju, a PRD, an architecture review, or the user's idea.

  2. Run a reality check. Scan for the five anti-patterns, then name the constraints they expose:

    • Vision without first step — sounds right, but nobody knows what to do this afternoon.
    • Fake migration plan — clean target, but the path assumes everything changes at once.
    • Unpriced risk — "we can refactor" with no cost on data loss, blast radius, missing tests, or hidden callers.
    • Long-term correct, short-term irresponsible — the full thing now would starve the current goal.
    • No stop rule — the plan can only continue; it cannot fail gracefully.

    Then answer: what real contracts constrain the work? What area carries the most blast radius? What assumptions are unproven? What part is mostly aesthetic, speculative, or premature? For the per-pattern counter-moves, read references/anti-patterns.md.

  3. Choose the minimum viable move. Pick one narrow vertical slice, proof point, or decision artifact. Define what it changes and what it refuses to change. Prefer something that creates evidence, not just more planning.

  4. Make verification explicit. Success criteria must be observable; failure signals must be named; the check must be cheap enough to run before confidence decays. If behavior needs to be driven by tests, route to hai-tdd.

  5. Cut scope aggressively. List what the first move should not attempt. Cut compatibility work not tied to a real contract, architecture polish that does not affect the proof point, and broad migration until the narrow slice is proven.

  6. Define the stop rule. What evidence would kill or pause this direction? What would force a smaller target? What can be rolled back or isolated? What decision should not be made yet?

Output

Produce the answer using references/output-template.md. Use its compact form for a quick feasibility question and the full section order for a substantial proposal or requested report.

Beyond the template's per-field shape, hold these constraints:

  • Lead with exactly one verdict — go / shrink / pause / reject / validate first — not with the analysis.
  • Name real constraints separately from anxiety or inertia.
  • Preserve the bold target when it is useful, but do not let it replace execution.
  • The default is a smaller proof, not paralysis. Do not turn goudi into "do nothing."
  • Do not write a giant plan; route to hai-goal when the output needs phases, todos, and execution tracking.

Route elsewhere when

  • The goal is to open the frame, escape compatibility fear, and think bigger — use geju. (goudi grounds an already opened frame; it does not open one.)
  • The question is whether the idea deserves doing at all — use hai-idea. goudi pressure-tests how to land a proposal, not whether it should exist.
  • Behavior needs to be driven by tests — use hai-tdd.
  • The output needs full phases, todos, and execution tracking — use hai-goal.

What This Skill Is Not

  • Not generic project management. It is a pressure test for whether a proposal can land.
  • Not anti-refactor and not timid. It rejects fantasy migrations, not clean targets — and the default is a smaller proof, not standing still.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Goudi AI skill do?

Pressure-tests an ambitious proposal and returns a landing judgment, one minimum viable proof, explicit cuts, success/failure signals, and a stop rule. Use when a direction has more vision than executable grounding or the user asks how to land it, reduce first-step scope, price risk, or define rollback(落地、别太飘、最小可行、止损). Use geju when the goal is to open the frame rather than ground an existing direction.

Why use Goudi on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hylarucoder/hai-stack/tree/main/skills/goudi. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Goudi?

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 Goudi?

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

Is the Goudi AI skill free?

It is published on GitHub by hylarucoder. 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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