Clean Room Boundary And Provenance

Community

Sahil-SS9

clean-room-boundary-and-provenance

Separate observation, specification and implementation.

Overview

Publisher	Sahil-SS9
Repository	`agent-personas`
Skill name	`clean-room-boundary-and-provenance`
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 Boundary And Provenance 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-boundary-and-provenance
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-boundary-and-provenance

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-boundary-and-provenance .claude/skills/clean-room-boundary-and-provenance

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

Use it in TypingMind

Enable Clean Room Boundary And Provenance 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 Boundary And Provenance 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 Boundary And Provenance 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 boundary and provenance

Keep observation and implementation contexts separate so a compatible implementation is based on behaviour and an independently reviewed specification. This is process guidance, not legal advice.

Gate before work

State the lawful authority, target, jurisdictions, licence/contract scope, intended distribution and excluded material. Escalate legal, anti-circumvention, trademark, asset and commercial-use questions to qualified counsel or the owner.

Two-context procedure

Create separate observation and implementation workspaces with access controls, timestamps and hashes.
Observation may record externally visible inputs, outputs, errors, state transitions, timing and environment. Do not transfer source code, decompiler text, non-public implementation detail, proprietary assets or expressive content.
Have an independent reviewer transform observations into a behaviour specification containing examples, invariants, tolerances and explicit unknowns.
Freeze the approved specification and clean/redistributable fixtures. The implementer works only from that packet.
Maintain a provenance ledger for every implementation decision: requirement ID, fixture, author, date, dependency licence and generated artefact hash.
Run a boundary audit before parity testing and again before release. Quarantine any contaminated packet; do not silently edit its history.

Verification

The implementation workspace must be reproducible from the approved specification and clean fixtures alone. The audit must list excluded material, unresolved questions, reviewers and corrective action. Never claim legal compliance or clean-room status merely because source files were not copied.

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 Boundary And Provenance AI skill do?

Separate observation, specification and implementation.

Why use Clean Room Boundary And Provenance on TypingMind?

Because you install it once and use it with any model. Clean Room Boundary And Provenance 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 Boundary And Provenance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Sahil-SS9/agent-personas/tree/main/skills/clean-room-boundary-and-provenance. 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 Boundary And Provenance?

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 Boundary And Provenance?

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

Is the Clean Room Boundary And Provenance 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.

View all

Pptx Author

NousResearch

OrganizationPopular

Build PowerPoint decks headless with python-pptx.

Stocks

Stock quotes, history, search, compare, crypto via Yahoo.

Lambda Labs

On-demand GPU cloud instances for ML training.

Modal

Serverless GPU cloud for ML jobs and model APIs.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Clean-room boundary and provenance

Gate before work

Two-context procedure

Verification

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now