Clean Room Implementation Workflow

Community

Sahil-SS9

clean-room-implementation-workflow

Build compatibility slices from a reviewed specification.

Overview

Publisher	Sahil-SS9
Repository	`agent-personas`
Skill name	`clean-room-implementation-workflow`
Stars	67
Forks	4
Bundled files	1
License	MIT
Links	Skill source Repository

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Sahil-SS9 on GitHub. Read the source before you install it.

Installation

Install the Clean Room Implementation Workflow AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Sahil-SS9/agent-personas/tree/main/skills/clean-room-implementation-workflow
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Sahil-SS9/agent-personas/tree/main/skills/clean-room-implementation-workflow

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/Sahil-SS9/agent-personas.git /tmp/agent-personas
mkdir -p .claude/skills
cp -r /tmp/agent-personas/skills/clean-room-implementation-workflow .claude/skills/clean-room-implementation-workflow

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Clean Room Implementation Workflow 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 Clean Room Implementation Workflow 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 Clean Room Implementation Workflow 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.

Clean-room implementation workflow

Build a compatible implementation in small vertical slices from a frozen behaviour specification. Do not author a clone from copied source or promise completeness without measurements.

Procedure

Select one requirement with a stable oracle and define the smallest useful slice.
Create a clean fixture and a failing parity test before implementation; retain the RED result as evidence.
Implement the narrowest public behaviour, with explicit error and state semantics. Keep reference observations out of source comments and runtime logs.
Run focused parity tests, then normal/boundary/malformed/negative-control cases. Record byte or semantic comparison mode and tolerances.
Add a second fixture before generalising. Track unsupported features rather than guessing.
Run differential, property and round-trip checks where applicable; minimise failures to a reproducible fixture.
Review dependency licences, generated artefacts and provenance before merging a slice.

Slice record

Requirement IDs; implementation commit; fixture hashes; environment; oracle; pass/fail; known divergence; performance/resource budget; reviewer; next slice.

Stop rules

Stop on contaminated inputs, unexplained parity failures, non-determinism, legal-scope uncertainty, or three identical failed approaches. Change the experiment, not the oracle. A high test count with weak oracles is not compatibility evidence.

Bundled files

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

NOTICE1 KB

Frequently asked questions

What does the Clean Room Implementation Workflow AI skill do?

Build compatibility slices from a reviewed specification.

Why use Clean Room Implementation Workflow on TypingMind?

Because you install it once and use it with any model. Clean Room Implementation Workflow 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 Clean Room Implementation Workflow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Sahil-SS9/agent-personas/tree/main/skills/clean-room-implementation-workflow. 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 Clean Room Implementation Workflow?

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 Clean Room Implementation Workflow?

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

Is the Clean Room Implementation Workflow AI skill free?

Yes. It is published on GitHub by Sahil-SS9 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Clean-room implementation workflow

Procedure

Slice record

Stop rules

Bundled files

Frequently asked questions

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