Open Science Skills
Open Science Skills is a library of 39 agentic skills for Claude Code, with a parallel 37-skill library for OpenAI Codex, written for computational social scientists and digital humanists. Each skill is meant to work the way the field expects: identify the data-generating process before proposing an estimator, design experiments and instruments to a standard, and hold drafts to established reporting norms.
The library follows the research lifecycle: survey design, list experiments, topic modeling, LLM text classification, VLM-based OCR pipelines, manuscript QA, multi-model orchestration, and transparent reporting under APSA, JARS, DA-RT, TOP, and FAIR expectations. Every skill is grounded in published methods sources and based on best practices for writing skills. See SOURCES.md for the bibliography of 150+ works consulted.
This is the toolkit I use in my own research, and it grows as I add sources and skills. The authoring is mine, with editing help from Opus 4.8, Fable 5, and ChatGPT 5.5/6.
| Platform | Skills | Invoke |
|---|---|---|
| Claude Code | 39, as the oss plugin |
/oss:skill-name |
| OpenAI Codex | 37, as the codex/ library |
$skill-name |
The two libraries differ only in invocation and tooling. The Codex side omits presubmit, fable-orchestrate, and opus-orchestrate, and adds 46-orchestrate; see codex/README.md.
Quick start · Skills · How skills trigger · Installation · Sources · Contributing · License
Quick start
Install the plugin from the marketplace (user-wide, all projects; add --scope project for one project only):
# Step 1: Register the marketplace (one-time)
claude plugin marketplace add scdenney/open-science-skills
# Step 2: Install the plugin
claude plugin install oss@open-science-skills
# Project-only install
claude plugin install oss@open-science-skills --scope project
Then invoke a skill explicitly, for example /oss:conjoint-design, or just describe your task in plain language and let the matching skill load on its own.
On Codex there is no plugin: install the skills library instead (see Codex).
Skills
Skills are grouped by where they fall in a project. Unless the Platform column says otherwise, a skill runs on both Claude Code (/oss:name) and Codex ($name). One row, 46-orchestrate, belongs to the Codex library only and is not part of the 39-skill plugin.
Project Setup
| Skill | Platform | Command | What it does |
|---|---|---|---|
| research-repo | Both | /oss:research-repo |
Scaffold a new research project around its source library, or audit an existing one, building the sources, references, and intake spine plus the analysis, manuscript, and review folders. |
Workflow & Orchestration
| Skill | Platform | Command | What it does |
|---|---|---|---|
| fable-orchestrate | Claude Code | /oss:fable-orchestrate |
Run a multi-model workflow with Fable 5 as lead: an Opus subagent takes heavy reasoning, a Sonnet subagent takes mechanical work, and a GPT-5.6 Codex peer gives a second opinion. |
| opus-orchestrate | Claude Code | /oss:opus-orchestrate |
The same workflow with Opus 4.8 as lead via ultracode (xhigh reasoning, dynamic Workflow fan-out). Opus reasons on hard problems itself and delegates only to fan out; the Codex peer is gpt-5.6-sol. |
| advisor | Both | /oss:advisor / $advisor |
Consult an independent second reviewer before committing to an interpretation or calling a task done. Fable 5 on Claude Code; this Codex library's GPT-5.6 advisor always runs Sol/xhigh. |
| 46-orchestrate | Codex | $46-orchestrate |
Sol/high owns orchestration, integration, and sign-off; it routes bounded work to Terra workers and reserves Luna for tightly specified mechanical work. |
Ideation
| Skill | Platform | Command | What it does |
|---|---|---|---|
| diverge | Both | /oss:diverge |
Before implementing, generate three to five distinct approaches labeled by how they differ, then pause for you to choose, instead of defaulting to the first obvious solution. |
| diverge-codex | Both | /oss:diverge-codex |
The same brainstorm-then-select, but Codex (GPT-5.6 Sol at xhigh, from Claude Code) generates the alternatives, so a second model family widens the range. |
Research Design
| Skill | Platform | Command | What it does |
|---|---|---|---|
| conjoint-design | Both | /oss:conjoint-design |
Design conjoint experiments: attribute construction, power analysis, and AMCE/AMIE estimation. |
| conjoint-diagnostics | Both | /oss:conjoint-diagnostics |
Check a conjoint design and its analysis for integrity, measurement error, external validity, and sound interpretation. |
| conjoint-cleaning | Both | /oss:conjoint-cleaning |
Reshape a Qualtrics conjoint export into analysis-ready long format, with choice mapping, translation, pilot detection, and validation. |
| survey-design | Both | /oss:survey-design |
Write survey instruments: question wording, scales, flow, pretesting, respondent burden, and social-desirability mitigation. |
| cross-national-design | Both | /oss:cross-national-design |
Design survey experiments that run across countries, covering per-country power, measurement equivalence, and instrument localization. |
| list-experiment | Both | /oss:list-experiment |
Design and diagnose list experiments (the item count technique), from sensitivity assessment through estimation and placebo checks. |
Analysis
| Skill | Platform | Command | What it does |
|---|---|---|---|
| topic-modeling | Both | /oss:topic-modeling |
Fit structural topic models: specification with covariates, topic-count selection by coherence and exclusivity, and reporting. |
| text-classification | Both | /oss:text-classification |
Classify text with LLMs: codebook design, human-in-the-loop workflows, validation, and agreement statistics. |
| model-council-voting | Both | /oss:model-council-voting |
Use a panel of models as independent coders, with consensus rules, chance-corrected agreement (Cohen, Fleiss, Krippendorff), and correlated-error checks. |
| model-committee | Both | /oss:model-committee |
Have GPT-5.6 Sol and Claude Opus 4.8 deliberate toward one decision: independent proposals, mutual critique, revision, and a pre-committed rule. Opus 4.8 chairs the tally. |
| model-committee-sol | Both | /oss:model-committee-sol |
The same committee, but the GPT debater is Terra (not Sol) and the chair is GPT-5.6 Sol rather than a member, so a model outside the vote runs the tally and synthesis. |
| model-committee-fable | Both | /oss:model-committee-fable |
The same committee, chaired by Fable 5: a lighter, faster chair that is not one of the two voting members. |
| llm-calibration-logprobs | Both | /oss:llm-calibration-logprobs |
Turn token log-probabilities into per-decision confidence, then measure calibration (ECE, Brier, reliability diagrams) against human labels. |
Corpus Processing
| Skill | Platform | Command | What it does |
|---|---|---|---|
| vlm-ocr-pipeline | Both | /oss:vlm-ocr-pipeline |
Build an OCR pipeline on vision-language models: model choice, image handling, prompts, batching, evaluation, and reproducibility. |
| post-ocr-cleanup | Both | /oss:post-ocr-cleanup |
Clean OCR output with LLM and rule-based correction, quality diagnostics, multilingual handling, and provenance tracking. |
| vlm-ocr-evaluation | Both | /oss:vlm-ocr-evaluation |
Compare OCR systems before a bulk run, using stratified ground truth and CER/WER reported per language and per stratum. |
Writing & Reporting
| Skill | Platform | Command | What it does |
|---|---|---|---|
| hypothesis-building | Both | /oss:hypothesis-building |
Turn a research question into falsifiable causal hypotheses using DAGs, counterfactuals, equivalence testing, and a stated smallest effect size of interest. |
| literature-review | Both | /oss:literature-review |
Build or audit a literature review: evidence map, closest-prior-work assessment, gap verdicts, and a synthesis plan. |
| narrative-building | Both | /oss:narrative-building |
Draft or audit a paper's introduction, moving from the "why" to the "if-then" and keeping multi-experiment papers coherent. |
| pre-registration-writing | Both | /oss:pre-registration-writing |
Write a pre-analysis plan: structure, registry choice, analysis strategy, and documentation of any deviations. |
| methods-reporting | Both | /oss:methods-reporting |
Check a methods section against CONSORT, JARS, and DA-RT with a 40-item reporting checklist. |
| paper-tex | Both | /oss:paper-tex |
Typeset a draft as house-style LaTeX from Markdown, Word, or other formats, build the PDF, and prepare it for a specific journal. |
Figures & Tables
| Skill | Platform | Command | What it does |
|---|---|---|---|
| figures | Both | /oss:figures |
Design publication-quality figures: chart choice, scales, color, legend order, self-contained captions, and reproducible code. |
| tables | Both | /oss:tables |
Design publication-quality tables: column order, row grouping, precision and uncertainty, self-contained notes, and reproducible code. |
Manuscript QA
| Skill | Platform | Command | What it does |
|---|---|---|---|
| fair-check | Both | /oss:fair-check |
Audit a finished manuscript against FAIR principles: data, code, and material availability, identifiers, licenses, and reuse conditions. |
| citation-check | Both | /oss:citation-check |
Check citations for in-text and reference parity, working DOIs, and fabrication risk (via Crossref and OpenAlex), plus citation style. |
| fact-check | Both | /oss:fact-check |
Verify that each in-text claim is actually supported by its cited source, reading the source's Markdown in the project's knowledge base. Runs citation-check first. |
| figure-table-audit | Both | /oss:figure-table-audit |
Audit the finished figure and table set for cross-references, text consistency, accessibility, and links to supplementary and replication materials. |
| replication-package | Both | /oss:replication-package |
Scaffold or audit a replication package: folder structure, README, master script, figure/table crosswalk, codebook, license, and pre-release checklist. |
Review & Submission
| Skill | Platform | Command | What it does |
|---|---|---|---|
| paper-review-lite | Both | /oss:paper-review-lite |
Run a pre-submission self-audit of your own manuscript across argument, numbers, references, writing, figures, and replication. |
| paper-review-lite-codex | Both | /oss:paper-review-lite-codex |
The same audit run across two model families: Claude and Codex (GPT-5.6 Sol at xhigh) review independently, then cross-check, and each surviving issue is tagged by confidence. |
| presubmit | Claude Code | /oss:presubmit |
Set up and run the standalone presubmit CLI, a heavier 30-plus-stage adversarial review pipeline driven by the Anthropic API. |
| journal-review | Both | /oss:journal-review |
Draft a senior referee report on someone else's manuscript, using parallel finder agents and a chief-reviewer synthesis to produce a structured report. |
How skills trigger
Most skills load on their own. When your prompt matches a skill's description, Claude Code or Codex reads that skill into context and follows it, so you usually don't need to name anything. You can also invoke any skill explicitly: /oss:skill-name in Claude Code, $skill-name in Codex.
The orchestration and delegated-review skills (fable-orchestrate, opus-orchestrate, 46-orchestrate, advisor, the model-committee family, diverge-codex, and paper-review-lite-codex) run only when invoked explicitly, because they start subagents or call an external model.
Installation
Claude Code
The recommended install is the plugin, shown in Quick start: it registers the marketplace and installs all 39 skills and their slash commands. The command prefix is oss: (open science skills); the marketplace and repository are named open-science-skills.
To try the plugin for one session without installing:
git clone https://github.com/scdenney/open-science-skills.git
cd open-science-skills && claude --plugin-dir ./plugin
Clone the repository and run the interactive installer, which lists the skills and installs your choices to ./.claude/skills/ (current project) by default:
git clone https://github.com/scdenney/open-science-skills.git
cd open-science-skills
bash plugin/scripts/install.sh
Other targets and non-interactive selection:
# Install to user-wide skills directory (all projects)
bash plugin/scripts/install.sh --target ~/.claude/skills
# Install specific skills non-interactively
bash plugin/scripts/install.sh --skill conjoint-design survey-design list-experiment
# Install all skills
bash plugin/scripts/install.sh --all --target ~/.claude/skills
Restart Claude Code after installing.
Copy the whole skill folder, since many skills ship reference, asset, or script files their SKILL.md points at (replace your-project with your project's path):
git clone https://github.com/scdenney/open-science-skills.git
# Project-level (current project only) — copy the whole skill folder:
# many skills ship reference/, assets/, or scripts/ files their SKILL.md points at
mkdir -p your-project/.claude/skills
cp -R open-science-skills/plugin/skills/conjoint-design \
your-project/.claude/skills/
# User-wide (all projects)
mkdir -p ~/.claude/skills
cp -R open-science-skills/plugin/skills/list-experiment ~/.claude/skills/
Manual copy gives auto-trigger only; slash commands require the plugin.
Codex
Codex discovers skills under .agents/skills (repository) and ~/.agents/skills (user-wide). From the repository root, install all 37 skills user-wide:
mkdir -p "$HOME/.agents/skills"
for skill in "$PWD"/codex/*/; do
ln -sfn "${skill%/}" "$HOME/.agents/skills/$(basename "$skill")"
done
For selective and repository-scoped install, plus the Codex catalog, see codex/README.md.
Knowledge base and sources
The skills are built from a curated corpus of methods texts rather than the model's built-in knowledge. SOURCES.md is the full bibliography (150+ works). The knowledge_base/ folder holds Markdown conversions of those sources that the skills read directly when a task needs chapter-and-verse support, as fact-check does when it verifies a claim against its citation.
Contributing
Pull requests are welcome. To add a skill:
- Write
plugin/skills/<name>/SKILL.md, following the skill authoring best practices. - Add
plugin/commands/<name>.md(a one-paragraph activation prompt plus$ARGUMENTS; see existing examples). - Mirror the skill to
plugin/.skills/<name>.md, byte-identical. - Add the Codex package at
codex/<name>/(SKILL.mdandagents/openai.yaml), unless the skill is intentionally platform-specific. - Add sources to
SOURCES.md. - Update the catalogs and badges, then run
bash plugin/scripts/check.sh.
License
This project is licensed under Creative Commons Attribution-NonCommercial 4.0 International. The skills are intended for noncommercial scholarly and educational use.
The citation-check, literature-review, figures, tables, and figure-table-audit skills remix workflow ideas from Cheng-I Wu's Academic Research Skills for Claude Code, also licensed CC BY-NC 4.0. The instructions here are rewritten for this repository's open-science and experimental-social-science scope.
The replication-package skill adapts the structural conventions in Yusaku Horiuchi's replication-package-guide (the source for single-entry-point, compact vs. build/analyze layouts, figure/table crosswalk, paper-consistency check, correction workflow, and pre-release checklist). FAIR-principle integration and Claude Code/Codex skill packaging are added on top; Harvard Dataverse and other platform-specific upload mechanics are not included. Cite Horiuchi's guide if you publish a package built with this skill.
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