A suite of recent data-science skills for Claude Code: ds-star & ds-star-plus (iterative plan→implement→execute→verify→route solving with a rubric-graded LLM-as-judge), ds-clarify (human-in-the-loop spec), ds-spike (multi-data-scientist ensemble with debate), ds-model (AIDE solution-tree + leaderboard), ds-conduct (data-aware orchestrator), ds-memory (cross-session memory), ds-verify/ds-reconcile/ds-vote/ds-search (standalone primitives), data-profile, and eda-narrative. Grounded in DS-STAR (Nam et al., 2025) and follow-on work.
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DS-STAR's single biggest correctness lever is analyzing every file *before* planning — its
Use when a data question is fuzzy or high-stakes — clarifies scope and writes analysis-spec.md before running a solver
Use when starting fresh with data and unsure which skills to use — peeks at data, asks targeted questions, assembles a crew plan
Use when setting up or repairing the Python env for analysis — detects uv/venv/conda/poetry/pipenv, installs core packages
Use when browsing, pruning, or seeding a run from past analyses stored across sessions
See the whole arc: Walkthrough — from a raw file to a reviewed answer — a messy real dataset, a vague goal, and the plugin catching a silent revenue error on the way to a defensible number. (To record your own terminal cast, see
docs/demo.md.)
14 slash commands that give Claude Code structured workflows for data science work — profiling, exploration, analysis, and model-building. The goal is a good kickoff: get from zero to a structured, executable, reviewed starting point in minutes rather than hours.
The contract. This is a kickoff tool, not an oracle.
- What it does: the mechanical work — profile the data, pin down the question, write and run the code, and check the result against common silent-failure modes.
- What it hands back to you: the judgment — the right question, the right data, the right interpretation — with the consequential scope decisions surfaced, not buried.
- When it stops and asks: ambiguous scope, contradictory requirements, or a domain judgment call. The cases it gets wrong are exactly the ones that warrant human or multi-agent review anyway — so it routes them to you instead of guessing.
→ Quickstart — one dataset, one command, expected output
Drop a data file in your project and use a slash command to kick off whatever you need:
/ds-conduct peeks at your data, asks a few questions, and assembles the right workflow automatically/data-profile gives you column stats, null rates, and join diagnostics before you write a single line/eda-narrative surfaces what's interesting and writes it up/ds-star-plus writes and runs Python iteratively, checks the result against 7 common failure modes (wrong column, dropped rows, unit mismatch, scope error, format mismatch, question substitution, missing output token), and backtracks if something's off/ds-spike runs 3 diverse solvers in parallel and reconciles them; useful when you need confidence or when two single runs disagreed/ds-model runs an AIDE-style solution tree with leakage and CV disciplineThe skills are prompts — structured workflows that guide Claude through a task. They don't replace your judgment; they give you a faster, more consistent starting point than writing the prompt from scratch each time.
claude plugin marketplace add AdamKrysztopa/ds-crew
# All your projects
claude plugin install ds-crew@ds-crew --scope user
# This project only (saved to .claude/settings.json)
claude plugin install ds-crew@ds-crew --scope project
# Local override, not committed
claude plugin install ds-crew@ds-crew --scope local
/ds-conduct # start here if you're not sure — inspects data, asks, routes
/ds-star-plus # iterative solver with rubric-graded verification
/ds-spike # 3 parallel solvers → consensus + minority report
/data-profile # data quality / profiling report
/eda-narrative # exploration → stakeholder narrative
/ds-star # baseline solver (paper-faithful, single model)
/ds-clarify # pin down intent before solving — writes analysis-spec.md
/ds-model # AutoML solution-tree with leakage/CV discipline
/ds-verify # grade any answer against the 7 DS failure modes
/ds-reconcile # reconcile multiple existing answers into consensus
/ds-vote # run same solver N times, take majority
/ds-search # MCTS tree-search for a task that keeps failing greedy
/ds-memory # remember and reuse recipes across sessions
/ds-env-setup # verify Python env, install packages, offer SessionStart hook
First time? Run
/ds-env-setupto verify your Python environment has the packages these skills need.
claude plugin update ds-crew@ds-crew
claude plugin uninstall ds-crew@ds-crew
After installing or updating: start a new Claude Code session (or
/restart) — the plugin cache loads at session start.
Not sure where to start? Run /ds-conduct or see docs/USAGE.md for a decision table.
npx claudepluginhub adamkrysztopa/ds-crew --plugin ds-crewA suite of architectural-decision skills for Claude Code: decide-architecture (software architecture stack), design-patterns (GoF + Python-idiomatic patterns), and agentic-patterns (LLM-agent control-flow design). Each skill branches on project status — greenfield runs a short selection interview and recommends a composed design; refactoring reviews existing code against the catalog and proposes targeted moves.
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A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Complete creative writing suite with 10 specialized agents covering the full writing process: research gathering, character development, story architecture, world-building, dialogue coaching, editing/review, outlining, content strategy, believability auditing, and prose style/voice analysis. Includes genre-specific guides, templates, and quality checklists.
UI/UX design intelligence. 67 styles, 161 palettes, 57 font pairings, 25 charts, 15 stacks (React, Next.js, Vue, Svelte, Astro, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui, Nuxt, Jetpack Compose). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient.
This skill should be used when users need to generate ideas, explore creative solutions, or systematically brainstorm approaches to problems. Use when users request help with ideation, content planning, product features, marketing campaigns, strategic planning, creative writing, or any task requiring structured idea generation. The skill provides 30+ research-validated prompt patterns across 14 categories with exact templates, success metrics, and domain-specific applications.
Develop, test, build, and deploy Godot 4.x games with Claude Code. Includes GdUnit4 testing, web/desktop exports, CI/CD pipelines, and deployment to Vercel/GitHub Pages/itch.io.