Finishing a Development Branch
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
A skill your agent uses when starting analysis work that needs isolation, or before executing a pre-registered plan - ensures an isolated, reproducible workspace with pinned environment, fixed…
Install Setting Up Reproducible Analysis
$ npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install K-Dense-AI/science-superpowers setting-up-reproducible-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/K-Dense-AI/science-superpowers.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/setting-up-reproducible-analysis .claude/skills/setting-up-reproducible-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "setting-up-reproducible-analysis" agent skill from https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/setting-up-reproducible-analysis into .claude/skills/setting-up-reproducible-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setting-up-reproducible-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/setting-up-reproducible-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install K-Dense-AI/science-superpowers setting-up-reproducible-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/science-superpowers.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/setting-up-reproducible-analysis .agents/skills/setting-up-reproducible-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "setting-up-reproducible-analysis" agent skill from https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/setting-up-reproducible-analysis into .agents/skills/setting-up-reproducible-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setting-up-reproducible-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install K-Dense-AI/science-superpowers setting-up-reproducible-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/science-superpowers.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/setting-up-reproducible-analysis .cursor/skills/setting-up-reproducible-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "setting-up-reproducible-analysis" agent skill from https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/setting-up-reproducible-analysis into .cursor/skills/setting-up-reproducible-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setting-up-reproducible-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/K-Dense-AI/science-superpowers.git --path skills/setting-up-reproducible-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install K-Dense-AI/science-superpowers setting-up-reproducible-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/science-superpowers.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/setting-up-reproducible-analysis .gemini/skills/setting-up-reproducible-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "setting-up-reproducible-analysis" agent skill from https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/setting-up-reproducible-analysis into .gemini/skills/setting-up-reproducible-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setting-up-reproducible-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install K-Dense-AI/science-superpowers setting-up-reproducible-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/K-Dense-AI/science-superpowers.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/setting-up-reproducible-analysis .github/skills/setting-up-reproducible-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "setting-up-reproducible-analysis" agent skill from https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/setting-up-reproducible-analysis into .github/skills/setting-up-reproducible-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setting-up-reproducible-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install K-Dense-AI/science-superpowers setting-up-reproducible-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/science-superpowers.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/setting-up-reproducible-analysis .opencode/skills/setting-up-reproducible-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "setting-up-reproducible-analysis" agent skill from https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/setting-up-reproducible-analysis into .opencode/skills/setting-up-reproducible-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setting-up-reproducible-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
setting-up-reproducible-analysis- GitHub stars
- 350
- Token cost
- ~1.5k tokens
- SKILL.md length
- 563 words
- Files
- 1
- Skills in repo
- 13
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
A skill your agent uses when starting analysis work that needs isolation, or before executing a pre-registered plan - ensures an isolated, reproducible workspace with pinned environment, fixed…
- Works in 6 steps: Detect Existing Isolation → Create Isolated Workspace → Pin the Environment → …
- Starting analysis work that needs isolation
- SKILL.md covers Overview, Step 0: Detect Existing…, Step 1: Create Isolated… and Step 2: Pin the Environment, plus 5 more sections
- Calls git, pip and conda
What it does
Setting Up Reproducible Analysis is an agent skill from K-Dense-AI/science-superpowers. 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
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Git worktrees and Reproducible research. It works with Git. The repository describes itself as: Composable computational-science methodology skills for AI research agents — pre-registration over TDD. A science-domain reimplementation of Superpowers.
When your agent uses it
- Starting analysis work that needs isolation
- Before executing a pre-registered plan - ensures an isolated
- Reproducible workspace with pinned environment
- Immutable raw data
Example prompts
- “/setting-up-reproducible-analysis”
Requirements
- Python 3
Workflow steps
6 steps, taken from the step headings in SKILL.md.
- Detect Existing Isolation
- Create Isolated Workspace
- Pin the Environment
- Fix Random Seeds
- Data Provenance & Immutability
- Verify a Clean Baseline
What it can do on your machine
Read from SKILL.md and the folder at commit 0374bdf. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
gitpipcondapytest
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git and pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Setting Up Reproducible Analysis loads about 1.5k tokens when it runs. Until then it costs about 59 tokens; SKILL.md has 563 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 563 words (~1,452 tokens).
“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.”
- name
- setting-up-reproducible-analysis
Files
Just SKILL.md in skills/setting-up-reproducible-analysis of K-Dense-AI/science-superpowers.
Open the folder on GitHubat commit 0374bdf
Compare with similar skills
Setting Up Reproducible Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Setting Up Reproducible Analysis this skillK-Dense-AI/science-superpowers | 350 | — | ~1.5k | Automated safety check: Pass | Custom licence | |
| Finishing a Development Branchobra/superpowers | 297k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Finishing A Development Branchfarm-fe/farm | 5.6k | 35 repos | ~1.8k | Automated safety check: Pass | MIT | |
| Git Worktree Cleanuplobehub/lobehub | 83k | — | ~2.8k | Automated safety check: Pass | Custom licence | |
| Pre-Release PR Triagejamiepine/voicebox | 57k | — | ~3.1k | Automated safety check: Pass | MIT | |
| Ccmanager Configkbwo/ccmanager | 1.3k | — | ~1.5k | Automated safety check: Pass | MIT |
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A skill your agent uses when a result is surprising, impossible, contradicts a sanity check, a pipeline fails, a model won't converge, or a replication fails - before adjusting anything
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Related
Works with
Categories
Questions about Setting Up Reproducible Analysis
What does Setting Up Reproducible Analysis do?
A skill your agent uses when starting analysis work that needs isolation, or before executing a pre-registered plan - ensures an isolated, reproducible workspace with pinned environment, fixed…. Setting Up Reproducible Analysis is an agent skill from K-Dense-AI/science-superpowers.
When should I use Setting Up Reproducible Analysis?
Setting Up Reproducible Analysis fits situations like: starting analysis work that needs isolation; before executing a pre-registered plan - ensures an isolated; reproducible workspace with pinned environment; immutable raw data.
How do I install Setting Up Reproducible Analysis in Claude Code?
Run `npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a claude-code`. Or copy the skill folder (skills/setting-up-reproducible-analysis in K-Dense-AI/science-superpowers) into .claude/skills/setting-up-reproducible-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Setting Up Reproducible Analysis in Codex?
Run `npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a codex`. Or copy the skill folder (skills/setting-up-reproducible-analysis in K-Dense-AI/science-superpowers) into .agents/skills/setting-up-reproducible-analysis in your project. Codex loads it when a task matches its description.
Can I use Setting Up Reproducible Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add K-Dense-AI/science-superpowers --skill setting-up-reproducible-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/setting-up-reproducible-analysis, .gemini/skills/setting-up-reproducible-analysis, .github/skills/setting-up-reproducible-analysis and .opencode/skills/setting-up-reproducible-analysis in your project.
What does Setting Up Reproducible Analysis need to run?
Going by SKILL.md and its folder, Setting Up Reproducible Analysis needs the command-line tools its instructions call (git, pip, conda and pytest). Our summary lists: Python 3.
Does Setting Up Reproducible Analysis access the network?
SKILL.md contains no URLs. Its commands use git and pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Setting Up Reproducible Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Setting Up Reproducible Analysis use?
Setting Up Reproducible Analysis has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Setting Up Reproducible Analysis use?
About 1.5k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Setting Up Reproducible Analysis?
Skills that share tags, products or a category with Setting Up Reproducible Analysis: Finishing a Development Branch (obra/superpowers, 297k stars), Finishing A Development Branch (farm-fe/farm, 5.6k stars), Git Worktree Cleanup (lobehub/lobehub, 83k stars) and Pre-Release PR Triage (jamiepine/voicebox, 57k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Setting Up Reproducible Analysis?
K-Dense-AI (a GitHub organization) maintains it in K-Dense-AI/science-superpowers, which has 350 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on September 13, 2026.
Source: K-Dense-AI/science-superpowers on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.