Godot Grill logo

Godot Grill

Community
jame581
godot-grill

Use when a new Godot system or feature has open design decisions — interrogates them in batched rounds, scope first, each question with a recommended answer, and records the answers before any design or code. Triggers on "grill me", "ask me first", "question me on the design", "what do I need to decide before building". Not for choosing between nodes or APIs, and not for bug fixes.

Overview

Publisherjame581
RepositoryGodotPrompter
Skill namegodot-grill
Stars
808
Forks
47
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 jame581 on GitHub. Read the source before you install it.

Installation

Install the Godot Grill 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/jame581/GodotPrompter/tree/master/skills/godot-grill
  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/jame581/GodotPrompter.git /tmp/GodotPrompter
mkdir -p .claude/skills
cp -r /tmp/GodotPrompter/skills/godot-grill .claude/skills/godot-grill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Godot Grill 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 Godot Grill 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 Godot Grill 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.

Godot Grill

Settle the decisions only the developer can make, before anyone designs a scene tree or writes code. The output is a decision record, not a design.

Related skills: godot-brainstorming for the scene tree, signal map, and plan once decisions are settled, scene-organization for composition vs. inheritance trade-offs, godot-mentor for teaching-mode delivery of what follows.

1. Decisions, not facts

Ask only what only the user knows: intent, constraints, priorities, taste.

Node types, API signatures, and version differences are facts. Look them up (godot-brainstorming/references/node-selection.md, the domain skills), decide, and record the choice. Never spend a question on one.

Architecture choices — data home, state representation, save format — are decided from the user's answers, not asked as technology picks. Ask the constraint behind them ("will designers edit items in the Inspector?"), then map the answer to Resource .tres yourself.

QuestionVerdict
"Throwaway prototype, or a system other code builds on?"Decision — ask
"Should the player be a CharacterBody2D or a RigidBody2D?"Fact — decide, record it
"When two clients disagree, who is right?"Decision — ask
"Can a Tween chain steps in 4.3?"Fact — never ask

2. The seeded dependency tree

Four roots have no prerequisites:

RootOptions
Scopethrowaway slice / one feature / a system others build on
Dimension2D / 3D / 2.5D
LanguageGDScript / C# / both
Authoritysingle-player / networked (and if networked, who is authoritative)
Settling this……unblocks
Scopeprunes branches: a throwaway slice skips persistence, data home, networking, and testing
Authoritystate ownership (source of truth); signals vs. RPCs
Dimensionphysics model; camera model
Languageinterop boundary, when the answer is "both"
Scope + Dimensionentity model: composition vs. inheritance
Entity modeldata home (Resource .tres / autoload / node-local @export); communication (signals up, calls down / EventBus / DI)
Authority + Entity modelstate representation (enum FSM / node FSM / AnimationTree / none); persistence boundary
Data home + Persistencesave format (ConfigFile / JSON / Resource serialization)

The right-hand column names what an answer lets you decide; ask the user the constraint behind it, never the technology. The tree is a seed, not a script. Answers grow it — "networked" creates branches a single-player answer never does. Skip any root the request or the project already answers (project.godot, existing scripts). Most sessions visit few nodes.

3. Rounds

Before round 1, read where the project keeps decision records, checking in order: the user's instructions or the project's agent instructions file (CLAUDE.md, AGENTS.md, …); then an existing decisions or ADR directory. A recorded decision is a settled prerequisite: never re-ask it; start the frontier past it.

The frontier is every open decision whose prerequisites are settled. Ask the whole frontier in one message, numbered, each with a recommended answer:

text
❓ **Q1** — **<title>**: <the question, with its options>

➡️ <recommended answer, and why in one clause>

Then stop and wait. A question whose prerequisite is still open belongs to a later round.

Round 1 is small and settles scope first — scope prunes the most tree. A "throwaway slice" answer commonly ends the session at round 2.

After each round, re-derive the frontier from the answers. If an answer contradicts a recorded decision, say so and ask whether to reopen it — never overwrite a record silently.

4. Ending the grill

The grill ends when the frontier is empty, or on the off-ramp: "just build it" / "skip the questions" / "stop grilling", in any round, including the first message. Then stop asking, and list every assumption you are now making for the open decisions, where the user can scan and overrule them.

On the off-ramp there are no confirmation or approval gates: list the assumptions, write the record, and build — with the matching domain skill, or godot-brainstorming from Step 2 without its per-section check-ins.

When the frontier empties, write the record (§5), confirm shared understanding in one message, and wait. Then hand off:

  • it needs a scene tree, signal map, or plan → godot-brainstorming, from Step 2
  • it is a single known change → the matching domain skill

5. The decision record

GodotPrompter has no decisions folder of its own. Write the record where this project keeps them, checking in order: the user's instructions or the project's agent instructions file (CLAUDE.md, AGENTS.md, …); then an existing decisions or ADR directory. If none applies, ask the user, suggesting docs/decisions/, or use docs/decisions/ when you cannot ask (a subagent or non-interactive run). Name the file YYYY-MM-DD-<topic>.md. The path must stay stable: the next grill reads it back.

markdown
# <Topic> — decisions

| Decision | Choice | Why | Revisit when |
|---|---|---|---|
| Bag model | Fixed 20 slots | Grid UI already designed | a weight system is wanted |
| Item data | Resource `.tres` | Inspector editing, typed exports | items exceed ~200 |

## Open / deferred
- Equipment stat aggregation — deferred to a later pass.
- Save slots — **assumed** 1 (off-ramp); revisit before shipping.

Revisit when keeps a decision reopenable, not binding. Off-ramp assumptions go under Open / deferred, marked assumed. If you cannot write files, put the record in your final message instead.

6. Anti-patterns

Anti-patternWhy it is wrongInstead
One question at a timeOrder fixed in advance; questions arrive before their prerequisites; more turnsAsk the whole frontier
Asking a factSpends the user's attention on the model's jobLook it up, decide, record
A question with no recommendationThe user answers in a vacuum; rounds slow downEvery question gets ➡️
Grilling a bug fix or an explicit askThe over-correction this skill must not becomeRoute to the domain skill
Re-asking a recorded decisionFeels like amnesia; wastes the recordRead where the project keeps decision records first
Coding after the last answerSkips the shared-understanding checkConfirm, then hand off

Checklist

  • Read existing decision records before round 1
  • Round 1 settled scope first
  • Every question is a decision — numbered, with a recommended answer
  • Whole frontier per round; waited after each
  • Off-ramp taken → assumptions listed
  • Record written (or in the final message when files cannot be written)
  • Frontier emptied → user confirmed before design or code; off-ramp → no gates, built on the listed assumptions

Frequently asked questions

What does the Godot Grill AI skill do?

Use when a new Godot system or feature has open design decisions — interrogates them in batched rounds, scope first, each question with a recommended answer, and records the answers before any design or code. Triggers on "grill me", "ask me first", "question me on the design", "what do I need to decide before building". Not for choosing between nodes or APIs, and not for bug fixes.

Why use Godot Grill on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jame581/GodotPrompter/tree/master/skills/godot-grill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Godot Grill?

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 Godot Grill?

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

Is the Godot Grill AI skill free?

Yes. It is published on GitHub by jame581 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 👇