Compound Health Data Science

Your AI research assistant — from research question to publication.

50 skills. 55 review agents. 35 reporting checklists. R and Python. Works with Claude Code, Codex, Pi, Gemini CLI, OpenCode, Kiro, and Qwen Code.

One plugin gives your coding agent the entire biomedical research lifecycle: frame your PICO, search PubMed, build cohorts, write your SAP, execute with tracking, review against STROBE/CONSORT/TRIPOD+AI, and document what you learned so the next study is easier.

How the package works

Get started like Compound Engineering

The normal path is intentionally short: install the plugin, start your agent, then run setup. For complete platform details, see docs/setup.md.

Choose your install route

From a source checkout, run bash install.sh doctor to see which local tools are available and the exact standard or locked-down route. Use the standard route on a personal or managed laptop that can run Git and the agent CLI. On a corporate or locked-down laptop, ask IT for the approved offline artifact and use the artifact-specific path below; Bun, Git, GitHub CLI, and Quarto are not required for basic use.

Claude Code, easiest path

macOS, Linux, WSL, or Git Bash:

git clone https://github.com/sajor2000/ce-datascience.git ~/ce-datascience
cd ~/ce-datascience
bash install.sh claude --aliases
claude

Windows PowerShell:

git clone https://github.com/sajor2000/ce-datascience.git "$HOME\ce-datascience"
cd "$HOME\ce-datascience"
.\install.ps1 claude -Aliases
claude

Then open the target project and run the native command:

/ce-datascience:ce-setup

The --aliases flag is optional; it installs safe local aliases so the demo-friendly bare /ce-* commands work. The namespaced command above is the reliable default for every native Claude plugin install.

Codex, easiest path

macOS, Linux, WSL, or Git Bash:

git clone https://github.com/sajor2000/ce-datascience.git ~/ce-datascience
cd ~/ce-datascience
bash install.sh codex
codex

Windows PowerShell:

git clone https://github.com/sajor2000/ce-datascience.git "$HOME\ce-datascience"
cd "$HOME\ce-datascience"
.\install.ps1 codex
codex

Inside Codex, open /plugins, install CE DataScience, restart Codex, then start a new thread and ask Codex to use CE DataScience for setup. The helper also installs the generated agent bridge when Bun is available.

Pi, generated install

Install Pi's two workflow extensions once, then generate the CE files into the Pi agent root:

pi install npm:pi-subagents
pi install npm:pi-ask-user
cd ~/ce-datascience
bun run src/index.ts install ./plugins/ce-datascience --to pi --pi-home "$HOME/.pi/agent"

Restart Pi, open the project, then invoke ce-setup with Pi's normal skill interface. pi-subagents is required for CE review/workflow delegation; pi-ask-user enables the short setup confirmation UI.

Use the plugin after installation

Installation makes CE DataScience available to the agent; setup configures it for each individual code or research project. After installing:

1. Restart Claude Code, Codex, or Pi so it loads the new plugin files.
2. Open the project or study directory you want CE DataScience to work on.
3. Configure that project with the setup skill.
4. Run the workflow skill to see the ordered research or engineering lifecycle and the next recommended skill.

In Claude Code, native plugin commands are namespaced:

/ce-datascience:ce-setup
/ce-datascience:ce-workflow

When --aliases or -Aliases was used, the shorter /ce-setup and /ce-workflow forms work too. In Codex, start a new task and say:

Use the CE DataScience ce-setup skill for this project.
Then use the CE DataScience ce-workflow skill and recommend the next step.

After that, request a specific skill in plain language or use its displayed name, for example ce-research-question, ce-data-qa, ce-plan, or ce-code-review. The plugin works in the currently open project; repeat setup when moving to a different project with a different stack or data layer.

Setup starts with one detected-profile summary instead of a full questionnaire. It shows inferred language, environment, reporting format, storage, and data domain with evidence, then offers Continue, Adjust, or Full survey. It asks only for values that are ambiguous or needed by the current workflow.

Locked-down or demo laptop

Use the offline release artifacts when package managers, GitHub CLI, Git, Bun, or Quarto are blocked by IT policy. Basic Claude Code and Codex use does not require Bun, GitHub CLI, or Quarto.

Claude Code can load the approved plugin folder or ZIP directly:

claude --plugin-dir /approved/path/ce-datascience
claude --plugin-dir /approved/path/ce-datascience.zip

Native Claude plugin skills are namespaced:

/ce-datascience:ce-setup --locked-down
/ce-datascience:ce-workflow

Bare /ce-* commands are an optional local alias layer, not a native plugin guarantee. Install them only when you want demo-friendly command names:

bash scripts/install/install-claude-aliases.sh --plugin-dir /approved/path/ce-datascience --scope user

For Codex without Bun, unpack ce-datascience-codex-local.zip and run:

bash install-codex-offline.sh --source /approved/path/ce-datascience-codex-local --codex-home "${CODEX_HOME:-$HOME/.codex}"

On Windows PowerShell, use the package's native installer:

.\install.ps1 codex -Source C:\approved\ce-datascience-codex-local -CodexHome "$HOME\.codex"

Restart Codex, open /plugins, install CE DataScience from the local marketplace, then restart again. The installer writes the personal marketplace file under .agents/plugins/marketplace.json and points it at ./.codex/plugins/ce-datascience relative to that marketplace root.

Recommended research add-ons

CE DataScience's bundled /ce-pubmed workflow works on its own. For agent-native PubMed, Europe PMC, MeSH, citation, and related-article tools, optionally add cyanheads/pubmed-mcp-server. For full-text synthesis, claim verification, figures, trials, regulatory documents, preprints, and biological databases, optionally add the Paperclip CLI and its official Paperclip skill, or its MCP server.

Start with PubMed MCP for lightweight biomedical discovery; add Paperclip when research planning needs deeper full-text or cross-source evidence. Neither is required or installed automatically. Review institutional privacy and network policy before connecting a hosted research service. See the optional research add-ons setup. The Paperclip skill is fetched and maintained by Paperclip, not bundled with CE DataScience. CE workflows currently auto-detect the Paperclip CLI only; external MCP or provider-skill results are direct agent capabilities, not automatic CE artifact handoffs.

Source checkout for contributors

Bun and Git are contributor/release tooling. Install them only when you need to build, validate, or convert the plugin from source:

curl -fsSL https://bun.sh/install | bash
export CE_DS_REPO="$HOME/ce-datascience"
git clone https://github.com/sajor2000/ce-datascience.git "$CE_DS_REPO"
cd "$CE_DS_REPO"
bun install

Launch Claude Code from the checkout:

claude --plugin-dir "$CE_DS_REPO/plugins/ce-datascience"

Pro tip — save yourself typing forever:

printf "\nalias claude-ds='claude --plugin-dir %s/plugins/ce-datascience'\n" "$CE_DS_REPO" >> ~/.zshrc
source ~/.zshrc

Now just type claude-ds in any project.

Configure your stack

/ce-datascience:ce-setup

Picks up your language (R or Python), IDE, libraries, and data layer automatically. It checks project evidence first and only asks questions that change generated config or workflow routing. If you installed optional aliases, /ce-setup works too.

See your workflow

/ce-datascience:ce-workflow

Shows every step for your project type and tells you what to do next. Each slash skill now starts with a Skill Value block that states the problem, expected output, question boundary, and non-goal so new users can pick the right command without guessing.

What can it do?

The examples below use bare /ce-* commands for readability. In native Claude plugin installs, use /ce-datascience:ce-* unless local aliases are installed.

Run an observational study

/ce-research-question "sepsis bundles and 30-day mortality in ICU"
/ce-pubmed
/ce-evidence-map
/ce-method-extract
/ce-checklist-match
/ce-effect-size
/ce-power
/ce-cohort-build
/ce-data-qa
/ce-plan
/ce-sap-tabular
/ce-sprint
/ce-work
/ce-verify
/ce-code-review
/ce-compound

Keep analysis decisions explicit

The lifecycle now makes the most consequential analytical assumptions visible before code is written or trusted:

• /ce-data-qa reconciles row counts and joins, checks keys and type stability, records missing-data handling, and returns GO, WARN, or NO-GO rather than silently substituting fallback data.
• /ce-plan and /ce-statistical-analysis-plan require the estimand, intended grain, keys, time zero, and success criteria for observational or causal work; unresolved choices remain questions for the analyst.
• /ce-work fails loudly at missing or corrupt inputs. /ce-code-review checks integrity and causal timing, and requires censoring-aware, decision-aligned time-dependent AUC for dynamic survival models.

For an administrative claims study, use the claims-oriented SAP workflow when you need a linked methods section, variables dictionary, analyses, diagnostics, outputs, and decision evidence:

/ce-statistical-analysis-plan

Build a prediction model

/ce-research-question
/ce-checklist-match
/ce-cohort-build
/ce-plan
/ce-ml-experiment-track
/ce-optimize
/ce-work
/ce-model-card
/ce-code-review

Work with CLIF consortium data

# Anchored to clif-icu.com; setup can infer a declared matching family.
# Use an explicit call when choosing the family for this task:
/ce-clif --version 2.1.0  # CLIF 2.1 + mCIDE 2.1
# or
/ce-clif --version 3.0.0  # CLIF 3.0 + mCIDE 3.0
/ce-workflow
/ce-work

If a direct call conflicts with an explicitly declared project pair, CE asks which source is intended before it validates categories or generates filters.

Analyze omics data

/ce-bioinfo-qc
/ce-genome-build
/ce-plan
/ce-work
/ce-code-review

Ship a software fix

/ce-brainstorm
/ce-plan
/ce-work
/ce-code-review

Maintain the plugin professionally

/ce-sessions
/ce-resolve-pr-feedback
/ce-release-notes
/ce-report-bug

These workflow utilities are adapted from the original compound-engineering plugin so the public plugin can support release questions, bug reports, cross-session debugging, and statistical-methodology PR feedback without pulling in unrelated Rails, frontend, Xcode, Slack, product-pulse, dogfood, LFG, or agent-native workflows.

Works with your stack

| Stack | IDE | Output | Libraries | |---|---|---|---| | Python + Jupyter | JupyterLab, VS Code | .ipynb | pandas, polars, scipy, statsmodels, scikit-learn | | Python + Marimo | Marimo, VS Code | reactive .py | pandas, polars, scipy, statsmodels, scikit-learn | | R | RStudio, VS Code | Quarto .qmd, .Rmd | tidyverse, data.table, survival, lme4, gt, tidymodels |

Knows your data layer

| Data layer | How it activates | What it does | |---|---|---| | OMOP CDM | SQL with cdm_source, concept, person | OMOP SQL + concept sets, vocabulary pinning | | CLIF | CLIF_CLAUDE.md, clif-icu remote, or CLIF handoff | Anchors to clif-icu.com; explicit CLIF/mCIDE 2.1 or 3.0 family, Parquet-only, version-correct mCIDE vocab, POC sign-off | | Admin claims | Medicare/Medicaid/MarketScan in code | Enrollment gaps, NDC-to-RxNorm, claims reviewer | | Custom EHR | Default | PHI scanning, generic cohort building | | Bioinformatics | .fastq, .bam, Snakefile | FastQC/MultiQC, genome build, batch-effect screen |

Upstream CE features now included

This fork tracks useful infrastructure and workflow improvements from the original compound-engineering plugin while keeping the product scoped to health data science.

| Area | What changed for data scientists | |---|---| | Planning and brainstorming | /ce-plan keeps SAP/implementation dual mode and now supports upstream output modes, HTML/Markdown rendering references, format-preserving resume, stronger synthesis, external-research routing, and conceptual-diagram affordances. /ce-brainstorm keeps study-design framing while adding grouped requirements, output-mode handling, and visual communication behavior. | | PR and review workflow | /ce-resolve-pr-feedback carries upstream GraphQL pagination and split-reference handling, then restores statistical methodology and SAP-aware response language. /ce-code-review, /ce-doc-review, /ce-commit, and /ce-commit-push-pr include shared workflow fixes where they improve review, commit, and PR hygiene. | | Session history | /ce-sessions uses upstream cross-platform discovery improvements for Claude Code, Codex, and Cursor sessions, with repo-root pre-resolution and structured extraction scripts. | | Distribution and installation | The converter supports current ce-*.md agent source files while still parsing legacy *.agent.md, respects CODEX_HOME, writes Codex roots correctly, and manages .codex/hooks.json without clobbering manual hooks. | | Public support | /ce-release-notes and /ce-report-bug are included as curated support skills for a professional public plugin surface. |

Core-only Compound Engineering skills such as Proof review, demo-reel capture, frontend/Rails/iOS helpers, LFG, simplify-code, strategy, promote, and polish remain external. When the core Compound Engineering plugin is also installed, ce-datascience handoffs can use those skills with a visible fallback; they are not packaged as ce-datascience slash skills.

Reviews against 35 checklists

| Study type | Primary | Extensions | |---|---|---| | Observational cohort | STROBE | RECORD, RECORD-PE, STROBE-MR, STREGA | | Randomized trial | CONSORT | CONSORT-AI, SPIRIT-AI, Cluster, Adaptive, N-of-1 | | Prediction model | TRIPOD, TRIPOD+AI | CHARMS | | Diagnostic accuracy | STARD, STARD-AI | CLAIM, QUADAS-2 | | Systematic review | PRISMA | DTA, NMA, IPD, ScR | | Target trial emulation | TARGET | | | Other | SQUIRE, GRAMMS, STaRT-RWE, ARRIVE, CARE, CHART, CHEERS, COREQ, DEAL, PDSQI, REFORMS | |

Also works with Codex, Pi, Gemini, and more

Run generated installs from the repo root (cd "$CE_DS_REPO"). Use ./plugins/ce-datascience with the leading ./ for local installs.

| Platform | Easiest command | |---|---| | Claude Code, one-command setup | bash install.sh claude --aliases then /ce-setup | | Claude Code, Windows PowerShell | .\install.ps1 claude -Aliases then /ce-setup | | Claude Code | claude --plugin-dir "$CE_DS_REPO/plugins/ce-datascience" then /ce-datascience:ce-setup | | Claude Code, offline | claude --plugin-dir /approved/path/ce-datascience.zip | | Claude bare aliases | bash scripts/install/install-claude-aliases.sh --plugin-dir "$CE_DS_REPO/plugins/ce-datascience" --scope user | | Codex, one-command setup | bash install.sh codex then install CE DataScience from /plugins | | Codex, Windows PowerShell | .\install.ps1 codex then install CE DataScience from /plugins | | Codex native + agent bridge | bun run src/index.ts install ./plugins/ce-datascience --to codex --codex-home "$CODEX_HOME" | | Codex offline local marketplace | bash install-codex-offline.sh --source /approved/path/ce-datascience-codex-local --codex-home "$CODEX_HOME" | | Codex standalone | bun run src/index.ts install ./plugins/ce-datascience --to codex --codex-home "$CODEX_HOME" --include-skills | | Pi | bun run src/index.ts install ./plugins/ce-datascience --to pi --pi-home "$HOME/.pi/agent" | | Gemini CLI | bun run src/index.ts install ./plugins/ce-datascience --to gemini --output /path/to/gemini-workspace | | OpenCode | bun run src/index.ts install ./plugins/ce-datascience --to opencode --output /path/to/workspace | | Kiro | bun run src/index.ts install ./plugins/ce-datascience --to kiro --output /path/to/kiro-workspace | | Qwen Code | qwen extensions install sajor2000/ce-datascience:ce-datascience | | All generated targets | bun run src/index.ts install ./plugins/ce-datascience --to all |

Pi also needs pi install npm:pi-subagents first. Qwen Code uses its native extension installer; it is not a generated --to qwen converter target. --to all only writes generated targets detected on the machine and skips native-only plugin ecosystems.

For a non-default Codex profile, point both Codex and the installer at the same root:

export CODEX_HOME="$HOME/.codex/profiles/research"
codex plugin marketplace add "$CE_DS_REPO"
cd "$CE_DS_REPO"
bun run src/index.ts install ./plugins/ce-datascience --to codex --codex-home "$CODEX_HOME"
CODEX_HOME="$CODEX_HOME" codex

Inside Codex, run /plugins, select this local marketplace, install ce-datascience, then restart. Codex's native plugin install provides the skills; the Bun command above adds generated agents until Codex supports plugin-defined agents natively.

Codex installs have two supported modes:

• Native plugin + agent bridge (recommended): install the plugin inside Codex with /plugins, then run install --to codex --codex-home "$CODEX_HOME" to add generated agents to the same profile.
• Standalone generated install: run bun run src/index.ts install ./plugins/ce-datascience --to codex --codex-home "$CODEX_HOME" --include-skills when native plugin install is unavailable. This writes generated skills, MCP config, and managed .codex/hooks.json entries.

Managed Codex hooks are tagged with plugin metadata so upgrades can replace this plugin's hook entries without deleting manual hooks or hooks owned by another plugin. If an existing hooks.json is malformed, the installer backs it up before writing a managed replacement.

See Codex profile and hook installation for the profile, standalone, and recovery details. See the setup guide for exact Claude, Codex, OpenCode, Gemini, Kiro, Pi, and Qwen walkthroughs.

Updating

cd ~/ce-datascience && git pull && bun install

Then restart your coding agent.

To build corporate/offline ZIPs from a source checkout:

bun run package:corporate

Troubleshooting

"Unknown command" on /ce-setup: Native Claude plugin commands are namespaced. Use /ce-datascience:ce-setup, or install the optional local aliases into .claude/commands.

bun install fails: Run bun --version. If missing: curl -fsSL https://bun.sh/install | bash

Corporate laptop blocks Bun, GitHub CLI, Git, or Quarto: Use the offline Claude folder/ZIP or Codex local marketplace package. Bun and Git are for source builds; GitHub CLI is only for GitHub helpers; Quarto is only required for Quarto render/manuscript workflows.

Plugin seems outdated: cd ~/ce-datascience && git pull && bun install, then restart.

Codex installed into the wrong profile: Set CODEX_HOME on both the codex command and the Bun installer. The installer defaults to $CODEX_HOME when set, otherwise ~/.codex.

Codex hooks stopped loading after a broken edit: Re-run the standalone install with --include-skills. The installer backs up malformed .codex/hooks.json before writing managed hook entries.

CLIF activating on a non-CLIF project: /ce-clif --off disables it for the session.

Full inventory

| | Count | |---|---| | Skills | 50 | | Agents | 55 | | Reporting checklists | 35 |

See every skill and agent

Built on

Fork of compound-engineering by Kieran Klaassen at Every. Also influenced by BMAD Method and Superpowers.

License

MIT — Copyright (c) 2026 Juan Carlos Rojas. Original compound-engineering Copyright (c) 2025 Every.