Review Ml Choices

Organization

probabl-ai

review-ml-choices

Show stored project choices and re-enter the skill that can change one. Trigger when the user asks what we decided, what the current settings are, or to change a stored project choice. SKIP an explicit sync, export, or “a constraint changed” request — those load sync-ml-reports, export-ml-project, or frame-ml-problem directly. HOW TO USE: run `review choices`, show that board, then load one owning skill. Do not policy set from here.

Overview

Publisher	probabl-ai
Repository	`skore-skills`
Skill name	`review-ml-choices`
Stars	144
Forks	9
Bundled files	1
License	BSD-3-Clause
Links	Skill source Repository Homepage

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 probabl-ai on GitHub. Read the source before you install it.

Installation

Install the Review Ml Choices 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/probabl-ai/skore-skills/tree/main/skills/review-ml-choices
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.

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/probabl-ai/skore-skills.git /tmp/skore-skills
mkdir -p .claude/skills
cp -r /tmp/skore-skills/skills/review-ml-choices .claude/skills/review-ml-choices

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

Use it in TypingMind

Enable Review Ml Choices 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 Review Ml Choices 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 Review Ml Choices 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.

Review ML Choices

Show stored choices. A change loads the skill that already owns that decision. Do not write .skore or the journal from here.

Human-facing prose

Details: setup-workspace references/human_facing_prose.md. The board uses data-science labels: where reports go, executed notebooks, documentation site, git commits, who manages the environment, data analysis, and each filled framing cell (prediction goal, deployment, metric, fold count, and the others below). Do not put skill ids, G-* names, or the wrapper CLI in the question.

Sequence

Run python -m skore_skills review choices. The JSON is the board. Do not rebuild which rows are offered. Do not run frame show or frame clear here.
AskUserQuestion, one pick. Say first, in 2–4 lines, what a change authorizes — re-entering that setup, not a silent flag flip — and echo the current values from the JSON. A file link is an addition, never the context.

Options are Keep these plus one option per changeable row and one option per framing row. read_only and not_offered are context, not options. Use each row's value. For not_offered, say that row's reason. When framing_reason is set, say it and do not offer framing rows. "Who manages the environment" is whether this project manages it (policy.env.managed). An installed skill is not that value. Do not write a skill id on the board.
Keep these → stop. Do not load a skill.
One changeable row → load that row's skill and stop. The close names the decision being re-opened, not the skill id. Do not policy set. Do not run the child's commands from memory.
- skore_mode → the user asked to change where reports go.
- notebooks_site → notebooks and the documentation site.
- git_autocommit → the user asked to change that choice.
- env_managed → do not run env add-skore here. If the recorded destination is hub or mlflow, do not use --mode local.
- data_analysis when action is rerun → do not write a JOURNAL skipped row. The written analysis stays; the change is to run it again.
One framing row → load frame-ml-problem naming that row's id. Do not blank the cell here.
A request to change a read_only row: say that row's reason and stop. Do not load setup-workspace to rename. Do not policy set.

Stop conditions

Do not policy set any key.
Do not edit JOURNAL, including a Data understanding skipped row.
Do not load sync-ml-reports when policy.skore_mode is unset.
Do not env add-skore, git commit, or scaffold src/.
If the owning skill is not installed, show the value and skip the change in one line. Do not invent that skill's steps.

Bundled files

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

evals/evals.json13 KB

Frequently asked questions

What does the Review Ml Choices AI skill do?

Why use Review Ml Choices on TypingMind?

Because you install it once and use it with any model. Review Ml Choices 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 Review Ml Choices in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/probabl-ai/skore-skills/tree/main/skills/review-ml-choices. 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 Review Ml Choices?

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 Review Ml Choices?

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

Is the Review Ml Choices AI skill free?

Yes. It is published on GitHub by probabl-ai under the BSD-3-Clause 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

Review ML Choices

Human-facing prose

Sequence

Stop conditions

Bundled files

Frequently asked questions

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