Agent skill · Data & Analytics

setting-up-reproducible-analysis

Use when starting analysis work that needs isolation, or before executing a pre-registered plan - ensures an isolated, reproducible workspace with pinned environment, fixed seeds, and immutable raw data

K-Dense-AIgithub.com/K-Dense-AIGitHub ↗
claude-codeNOASSERTION
Install
npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Path: skills/setting-up-reproducible-analysis/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 280
Language: Shell

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Setting Up a Reproducible Analysis ## Overview Ensure the analysis happens in an isolated workspace that another person (or future you) can reproduce exactly: same code, same environment, same seed, same immutable input data. **Core principle:** A result you cannot reproduce is not a result. Set up reproducibility before you run anything. **Announce at start:** "I'm using the setting-up-reproducible-analysis skill to set up an isolated, reproducible workspace." ## Step 0: Detect Existing Isolation Before creating anything, check whether you're already in an isolated workspace. ```bash GIT_DIR=$(cd "$(git rev-parse --git-dir)" 2>/dev/null && pwd -P) GIT_COMMON=$(cd "$(git rev-parse --git-common-dir)" 2>/dev/null && pwd -P) BRANCH=$(git branch --show-current) ``` **Submodule guard:** `GIT_DIR != GIT_COMMON` is also true in submodules. Verify you're not in one: ```bash git rev-parse --show-superproject-working-tree 2>/dev/null ``` **If `GIT_DIR != GIT_COMMON` (and not a submodule):** already in a linked worktree. Skip to Step 2 (Environment). Don't create another. **If `GIT_DIR == GIT_COMMON`:** normal checkout. If your human partner hasn't already stated a preference, ask before cr

What's inside
Steps it walks through
  1. Overview
  2. Step 0: Detect Existing Isolation
  3. Step 1: Create Isolated Workspace
  4. Step 2: Pin the Environment
  5. Step 3: Fix Random Seeds
  6. Step 4: Data Provenance & Immutability
  7. Step 5: Verify a Clean Baseline
  8. Report
  9. Quick Reference
  10. Red Flags
Commands it runs
git rev-parse --show-superproject-working-tree 2>/dev/null
Prefer an existing .worktrees/ (must be git-ignored), else default to it
git check-ignore -q .worktrees 2>/dev/null || echo ".worktrees/" >> .gitignore
git worktree add ".worktrees/$BRANCH_NAME" -b "$BRANCH_NAME"
cd ".worktrees/$BRANCH_NAME"
Python
if [ -f environment.yml ]; then conda env create -f environment.yml || conda env update -f environment.yml; fi
if [ -f requirements.txt ]; then python -m venv .venv && . .venv/bin/activate && pip install -r requirements.txt; fi
if [ -f pyproject.toml ]; then python -m venv .venv && . .venv/bin/activate && pip install -e .; fi
R
More from science-superpowers
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About this skill
What does the setting-up-reproducible-analysis skill do?

Use when starting analysis work that needs isolation, or before executing a pre-registered plan - ensures an isolated, reproducible workspace with pinned environment, fixed seeds, and immutable raw data

How do I install it?

Run `npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From K-Dense-AI/science-superpowers, a repository with 280 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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