Updated 1mo ago
by K-Dense-AI
science-superpowers
Composable computational-science methodology skills for AI research agents — pre-registration over TDD. A science-domain reimplementation of Superpowers.
357 GitHub stars (357)
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- 16 skills (16 skills found in its SKILL.md files)
- 36 forks (36 forks)
- 1mo ago last update (Last updated 1mo ago)
Install
Skills CLI
npx skills add K-Dense-AI/science-superpowers
Asks which skills and agents to install. Just one: npx skills add K-Dense-AI/science-superpowers --skill designing-the-analysis — add -g for every project.
Claude Code
git clone https://github.com/K-Dense-AI/science-superpowerscp -r "science-superpowers/skills/designing-the-analysis" ~/.claude/skills/
Copies the designing-the-analysis skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.
Plugin
/plugin marketplace add K-Dense-AI/science-superpowers
Run inside Claude Code if the repository ships a plugin marketplace, then pick plugins from /plugin.
Skills can run code on your machine — read the SKILL.md first.
What it does
In the author's own words, from each skill's SKILL.md.
-
designing-the-analysis
Use when you have an approved research question and need a concrete analysis plan, before touching outcome data or fitting any model
skills/designing-the-analysis/SKILL.md on GitHub (opens in a new tab) -
dispatching-parallel-investigations
Use when facing 2+ independent investigations that can proceed without shared state - parallel literature survey, multi-dataset replication, or pre-specified robustness checks
skills/dispatching-parallel-investigations/SKILL.md on GitHub (opens in a new tab) -
establishing-feasibility-first
Use when your human partner has explicitly opted into exploratory or feasibility mode - a compute-heavy simulation, an unproven pipeline, an unbenchmarked solver, an untested cluster job - or when whether the work can run at all is still unknown, when a plan's largest configuration has never been executed, when a memory or wall-clock ceiling is estimated rather than measured, or when someone prop…
skills/establishing-feasibility-first/SKILL.md on GitHub (opens in a new tab) -
executing-analysis
Use when you have a pre-registered analysis plan to execute inline in this session with review checkpoints, on a platform without subagents
skills/executing-analysis/SKILL.md on GitHub (opens in a new tab) -
framing-research-questions
You MUST use this before any data analysis or investigation - before exploring a dataset, loading or profiling data, running a model, computing a statistic, or testing an idea, and before any outcome data is touched
skills/framing-research-questions/SKILL.md on GitHub (opens in a new tab) -
investigating-anomalous-results
Use 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
skills/investigating-anomalous-results/SKILL.md on GitHub (opens in a new tab) -
preregistering-analysis
Use before running any confirmatory analysis or looking at outcome data, when testing a hypothesis, computing a p-value, or about to claim an effect - locks predictions and decision rules before results are seen
skills/preregistering-analysis/SKILL.md on GitHub (opens in a new tab) -
receiving-critical-review
Use when receiving critical feedback on an analysis or manuscript, before implementing suggestions, especially if feedback seems unclear or methodologically questionable - requires verification, not performative agreement or blind changes
skills/receiving-critical-review/SKILL.md on GitHub (opens in a new tab) -
reporting-and-archiving-findings
Use when an analysis is complete and verified, and you need to decide how to report it and archive the work for reproducibility
skills/reporting-and-archiving-findings/SKILL.md on GitHub (opens in a new tab) -
requesting-red-team-review
Use after completing an analysis or before reporting a finding, to have a skeptical reviewer attack the conclusion before you believe it
skills/requesting-red-team-review/SKILL.md on GitHub (opens in a new tab) -
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
skills/setting-up-reproducible-analysis/SKILL.md on GitHub (opens in a new tab) -
subagent-driven-analysis
Use when executing a pre-registered analysis plan with mostly independent steps in the current session
skills/subagent-driven-analysis/SKILL.md on GitHub (opens in a new tab) -
surveying-prior-work
Use after framing a question and before designing an analysis, or when choosing a method, judging whether a result is novel, or needing a prior effect size for a power calculation
skills/surveying-prior-work/SKILL.md on GitHub (opens in a new tab) -
using-science-superpowers
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
skills/using-science-superpowers/SKILL.md on GitHub (opens in a new tab) -
verifying-results-before-claiming
Use when about to claim a result, effect, significance, or that an analysis reproduces, before reporting or writing it up - requires running the analysis fresh and reading the actual output first; evidence before claims always
skills/verifying-results-before-claiming/SKILL.md on GitHub (opens in a new tab) -
writing-science-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment
skills/writing-science-skills/SKILL.md on GitHub (opens in a new tab)
No skill matches that filter.
Review before you install
A skill is a set of instructions and scripts your agent will follow, and it can run code on your machine. Read the SKILL.md and any scripts first — this listing is not a security review.
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