Matlab
zLanqing/codex-claude-academic-skills
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing.
A skill your agent uses when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and…
Install Jcp Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jcp-data-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/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis .claude/skills/jcp-data-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 "jcp-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis into .claude/skills/jcp-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jcp-data-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/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-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 brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jcp-data-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis .agents/skills/jcp-data-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 "jcp-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis into .agents/skills/jcp-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jcp-data-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 brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jcp-data-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis .cursor/skills/jcp-data-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 "jcp-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis into .cursor/skills/jcp-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jcp-data-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/brycewang-stanford/Awesome-Journal-Skills.git --path Journal-of-Consumer-Psychology-Skills/skills/jcp-data-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 brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jcp-data-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis .gemini/skills/jcp-data-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 "jcp-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis into .gemini/skills/jcp-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jcp-data-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 brycewang-stanford/Awesome-Journal-Skills jcp-data-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 brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis .github/skills/jcp-data-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 "jcp-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis into .github/skills/jcp-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jcp-data-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 brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-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 brycewang-stanford/Awesome-Journal-Skills jcp-data-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis .opencode/skills/jcp-data-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 "jcp-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis into .opencode/skills/jcp-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jcp-data-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
jcp-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 685 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and…
- Analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect
- SKILL.md covers When to trigger, Analyze the process, not just…, The analysis toolkit by link… and Measuring the psychological…, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Measured and experimental mediation
What it does
Jcp Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and moderated mediation, measurement of the process, and the rigor-era reporting standards. Analyzes the studies; it does not design them (jcp-methods).
Its SKILL.md is about 1.6k 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 Data & Analytics, covering Statistics, Dispute resolution and Data analysis. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect
- Measured and experimental mediation
- Moderation and moderated mediation
- Measurement of the process
Example prompts
- “/jcp-data-analysis”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. 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
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Jcp Data Analysis loads about 1.6k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 685 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
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 685 words, ~1,634 tokens.
Download SKILL.mdSave it as
.claude/skills/jcp-data-analysis/SKILL.md (or your agent's skills folder).- name
- jcp-data-analysis
- description
- Use when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and moderated mediation, measurement of the process, and the rigor-era reporting standards. Analyzes the studies; it does not design them (jcp-methods).
Data Analysis (jcp-data-analysis)
When to trigger
- Your effect is significant but the process evidence does not yet hold up
- You ran mediation but a reviewer calls it correlational or under-powered
- A moderation is predicted but the interaction is messy or the simple effects are not probed
- You need to report results to JCP's post-rigor-reform standards (effect sizes, CIs, exclusions)
- The measure of your psychological process is noisy or its validity is in question
Analyze the process, not just the p-value
JCP's contribution is a mechanism, so the analysis must make the process visible and defensible. The headline test of the effect (typically ANOVA or regression with the manipulated IV) is necessary but not sufficient; the paper lives or dies on whether the mediation/moderation evidence supports the proposed psychological process and rules out rivals. Report estimates with effect sizes and confidence intervals, exact statistics, and full Ns before and after pre-specified exclusions. APA reporting style is the house norm.
The analysis toolkit by link in the chain
| Link | Standard analysis | What reviewers look for |
|---|---|---|
| Existence of effect | t-test / ANOVA / OLS with the manipulated IV | clean cells, effect size (d, η²), CI, no covariate fishing |
| Measured mediation | bootstrapped indirect effect (e.g., PROCESS / lavaan), bias-corrected CI | indirect effect with CI excluding 0; honesty that this is correlational evidence on the mediator |
| Experimental mediation | causal-chain design or manipulated-mediator analysis | the manipulation of M moves Y as the theory predicts |
| Moderation | regression interaction; ANOVA factorial | interaction term + probed simple effects (spotlight/floodlight), not just a significant interaction |
| Moderated mediation | conditional indirect effects (index of moderated mediation) | the index, with CI, and conditional indirect effects by moderator level |
Prefer experimental/causal-chain mediation and moderation-of-process over measured-mediator-only inference: JCP reviewers now treat a bootstrapped indirect effect on a self-reported mediator as suggestive, not dispositive, because it cannot establish the causal direction of M → Y.
Measuring the psychological process
- Validate the mediator measure: report reliability (α/ω) for multi-item scales; show the measure captures the intended construct and discriminates from confounds (mood, arousal, difficulty).
- Rule out alternative mediators statistically: include rival process measures and show the focal mediator carries the effect when they are modeled together.
- Avoid mediator-as-manipulation-check confusion: a manipulation check is not a mediator; the mediator is the downstream mental state.
Rigor-era reporting (post-2010s consumer-psych reforms)
- Report exact test statistics, p-values, effect sizes, and CIs — not just "p < .05."
- Disclose all conditions and measures collected; do not hide arms (the disclosure norm).
- Report sample size determination and adherence to (or deviation from) the pre-registration.
- State exclusions and their rule transparently, with Ns before/after.
- Avoid asterisk-only tables; report the numbers a reader needs to assess the process.
Show full SKILL.md (248 more words)Show less
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JCP is experimental consumer psychology; randomization inference, mediation done right (mediate, not naive controlling-away), and family-wise corrections matter most.
- Many outcomes / specifications:
romano_wolf(step-down FWER) orbenjamini_hochberg— report the adjusted threshold. - OVB sensitivity:
oster_delta/sensemakr. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley; multilevel data → cluster at the right level. - Re-fit off one handle:
audit_result(result_id)lists the missing checks and the exactsuggest_functionfor each. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Keep the decisive checks in the body and the exhaustive battery in the appendix. See the executed chain in the JF execution walkthrough.
Checklist
- Effect reported with exact stats, effect size, and CI; cells and Ns clear
- Mediation uses bootstrapped/bias-corrected CIs; measured-only mediation is labeled correlational
- At least one stronger-than-Baron-Kenny process test where the claim is causal
- Moderation: interaction reported and simple effects probed (spotlight/floodlight)
- Moderated mediation: index of moderated mediation + conditional indirect effects
- Mediator measure reliability reported; rival mediators modeled and ruled out
- Exclusions pre-specified; all conditions/measures disclosed; preregistration deviations noted
Anti-patterns
- Indirect-effect worship: a significant bootstrapped indirect effect treated as proof of causal process
- Interaction without simple effects: a significant interaction with no spotlight/floodlight probing
- Covariate fishing: adding controls until the effect appears, undisclosed
- Hidden arms: dropping conditions or DVs that didn't work without reporting them
- p-only reporting: asterisks instead of effect sizes and CIs
- Mediator confound: a "mediator" that is just mood/difficulty the manipulation also moved
Output format
【Effect】test, stat, effect size, CI, cell Ns
【Mediation】measured / experimental; indirect effect + CI; correlational caveat if measured-only
【Moderation】interaction + probed simple effects (spotlight/floodlight)
【Moderated mediation】index + conditional indirect effects (if applicable)
【Process measure】reliability + rival mediators ruled out
【Rigor disclosures】exclusions, all conditions/measures, preregistration deviations
【Next skill】jcp-contribution-framing© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jcp Data 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 |
|---|---|---|---|---|---|---|
| Jcp Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| MatlabzLanqing/codex-claude-academic-skills | 4.6k | 9 repos | ~2.3k | Automated safety check: Notes | GPL-3.0 | |
| Eqtl Catalogue Region FetchClawBio/ClawBio | 1.2k | 1 repos | ~4.3k | Automated safety check: Pass | MIT | |
| CSV Data Analysis5zjk5/prompt-engineering | 127 | — | ~2.6k | Automated safety check: Pass | None | |
| Meridian MMM Model Buildinggoogle/meridian | 1.6k | — | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Gwas Catalog Region FetchClawBio/ClawBio | 1.2k | 1 repos | ~3.5k | Automated safety check: Pass | MIT |
Similar skills
Eqtl Catalogue Region Fetch
ClawBio/ClawBio
Fetch a region of cis-eQTL summary statistics from EBI eQTL Catalogue v7+ via tabix-on-FTP.
CSV Data Analysis
5zjk5/prompt-engineering
This skill should be used when users need to analyze CSV or Excel files, understand data patterns, generate statistical summaries, or create data visualizations.
- Official
Meridian MMM Model Building
google/meridian
Takes a user through building a Meridian marketing mix model, from loading CSV data and mapping columns to running EDA, fitting and saving the model.
Gwas Catalog Region Fetch
ClawBio/ClawBio
Fetch a region of GWAS summary statistics from the NHGRI-EBI GWAS Catalog harmonised collection via tabix-on-FTP.
Statistical Data Analysis
lingzhi227/agent-research-skills
Writes statistical analysis code for experimental data, runs it through a four-round review, and reports effect sizes, p-values and confidence intervals.
More from brycewang-stanford/Awesome-Journal-Skills
All 2,387 skills in this repoAaag Data Analysis
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…
Aaag Literature Positioning
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…
Aaag Rebuttal
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…
Aaag Research Design
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…
Aaag Review Process
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…
Aaag Submission
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…
Related
Categories
Questions about Jcp Data Analysis
What does Jcp Data Analysis do?
A skill your agent uses when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and…. Jcp Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and moderated mediation, measurement of the process, and the rigor-era reporting standards.
When should I use Jcp Data Analysis?
Jcp Data Analysis fits situations like: analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect; measured and experimental mediation; moderation and moderated mediation; measurement of the process.
How do I install Jcp Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-analysis -a claude-code`. Or copy the skill folder (Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jcp-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Jcp Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-analysis -a codex`. Or copy the skill folder (Journal-of-Consumer-Psychology-Skills/skills/jcp-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jcp-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Jcp Data 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 brycewang-stanford/Awesome-Journal-Skills --skill jcp-data-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/jcp-data-analysis, .gemini/skills/jcp-data-analysis, .github/skills/jcp-data-analysis and .opencode/skills/jcp-data-analysis in your project.
What does Jcp Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Jcp Data Analysis is instructions for the agent only.
Does Jcp Data Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Jcp Data 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 Jcp Data Analysis use?
Jcp Data Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Jcp Data Analysis use?
About 1.6k tokens (SKILL.md is roughly 6.5k 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 Jcp Data Analysis?
Skills that share tags, products or a category with Jcp Data Analysis: Matlab (zLanqing/codex-claude-academic-skills, 4.6k stars), Eqtl Catalogue Region Fetch (ClawBio/ClawBio, 1.2k stars), CSV Data Analysis (5zjk5/prompt-engineering, 127 stars) and Meridian MMM Model Building (google/meridian, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jcp Data Analysis?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.