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.
Systematic experimental results analysis workflow for ML/AI research papers.
Install Scholar Experiment
$ npx skills add catlog22/maestro-flow --skill scholar-experiment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install catlog22/maestro-flow scholar-experiment --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/catlog22/maestro-flow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/optional/skills/scholar-experiment .claude/skills/scholar-experiment && 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 "scholar-experiment" agent skill from https://github.com/catlog22/maestro-flow/tree/master/optional/skills/scholar-experiment into .claude/skills/scholar-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scholar-experiment", 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/catlog22/maestro-flow/tree/master/optional/skills/scholar-experimentType 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 catlog22/maestro-flow --skill scholar-experiment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install catlog22/maestro-flow scholar-experiment --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/maestro-flow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/optional/skills/scholar-experiment .agents/skills/scholar-experiment && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "scholar-experiment" agent skill from https://github.com/catlog22/maestro-flow/tree/master/optional/skills/scholar-experiment into .agents/skills/scholar-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scholar-experiment", 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 catlog22/maestro-flow --skill scholar-experiment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install catlog22/maestro-flow scholar-experiment --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/maestro-flow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/optional/skills/scholar-experiment .cursor/skills/scholar-experiment && 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 "scholar-experiment" agent skill from https://github.com/catlog22/maestro-flow/tree/master/optional/skills/scholar-experiment into .cursor/skills/scholar-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scholar-experiment", 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/catlog22/maestro-flow.git --path optional/skills/scholar-experiment--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 catlog22/maestro-flow --skill scholar-experiment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install catlog22/maestro-flow scholar-experiment --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/maestro-flow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/optional/skills/scholar-experiment .gemini/skills/scholar-experiment && 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 "scholar-experiment" agent skill from https://github.com/catlog22/maestro-flow/tree/master/optional/skills/scholar-experiment into .gemini/skills/scholar-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scholar-experiment", 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 catlog22/maestro-flow scholar-experimentInstalls 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 catlog22/maestro-flow --skill scholar-experiment -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/catlog22/maestro-flow.git skills-src && mkdir -p .github/skills && cp -r skills-src/optional/skills/scholar-experiment .github/skills/scholar-experiment && 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 "scholar-experiment" agent skill from https://github.com/catlog22/maestro-flow/tree/master/optional/skills/scholar-experiment into .github/skills/scholar-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scholar-experiment", 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 catlog22/maestro-flow --skill scholar-experiment -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install catlog22/maestro-flow scholar-experiment --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/catlog22/maestro-flow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/optional/skills/scholar-experiment .opencode/skills/scholar-experiment && 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 "scholar-experiment" agent skill from https://github.com/catlog22/maestro-flow/tree/master/optional/skills/scholar-experiment into .opencode/skills/scholar-experiment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scholar-experiment", 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
scholar-experiment- GitHub stars
- 564
- Token cost
- ~3.4k tokens
- SKILL.md length
- 878 words
- Files
- 6
- Skills in repo
- 30
- Repo updated
- First seen
- Licence
- None found
At a glance
Systematic experimental results analysis workflow for ML/AI research papers.
- Works in 5 steps: Data Loading → Statistical Analysis → Visualization → …
- Analyze experimental results
- SKILL.md covers Pre-load (before execution), Architecture Overview, Key Design Principles and Statistical Tools and Libraries, plus 10 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Scholar Experiment is an agent skill from catlog22/maestro-flow. Systematic experimental results analysis workflow for ML/AI research papers. Connects experimental data to publication-ready Results sections with statistical validation, visualizations, and quality checks. Triggers on "analyze experimental results", "generate results section", "statistical analysis of experiments", "compare model performance", "create results visualization".
Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files (for example `phases/01-data-loading.md`, `phases/02-statistical-analysis.md` and `phases/03-visualization.md`).
It sits in Data & Analytics, covering Statistics. The repository describes itself as: Intent-driven workflow orchestration for multi-agent AI development — adaptive lifecycle engine, self-reinforcing knowledge graph, and visual dashboard for Claude Code, Gemini….
When your agent uses it
- Analyze experimental results
- Generate results section
- Statistical analysis of experiments
- Compare model performance
Example prompts
- “analyze experimental results”
- “generate results section”
- “statistical analysis of experiments”
- “/scholar-experiment”
Requirements
- Python 3
- Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep, AskUserQuestion, TodoWrite
Workflow steps
5 steps, taken from the step headings in SKILL.md.
- Data Loading
- Statistical Analysis
- Visualization
- Results Writing
- Quality Check
What it can do on your machine
Read from SKILL.md and the folder at commit af37312. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditBashGlobGrepAskUserQuestionTodoWrite
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python, r and javascript).
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
Scholar Experiment loads about 3.4k tokens when it runs. Until then it costs about 99 tokens; SKILL.md has 878 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Read, Write, Edit, Bash, Glob, Grep, AskUserQuestion, TodoWrite
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
Without a licence we can't republish the file, so here is its outline and opening line. It has 878 words (~3,419 tokens).
“A systematic workflow for analyzing ML/AI experimental results and generating publication-ready Results sections. Transforms raw experimental data into validated statistical analyses, publication-quality visualizations, and well-structured paper content.”
- name
- scholar-experiment
- allowed-tools
- Read, Write, Edit, Bash, Glob, Grep, AskUserQuestion, TodoWrite
- disable-model-invocation
- true
- session-mode
- none
Files
SKILL.md and 5 other files in optional/skills/scholar-experiment of catlog22/maestro-flow.
- SKILL.md
- phases/01-data-loading.md
- phases/02-statistical-analysis.md
- phases/03-visualization.md
- phases/04-results-writing.md
- phases/05-quality-check.md
Open the folder on GitHubat commit af37312
Compare with similar skills
Scholar Experiment 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 |
|---|---|---|---|---|---|---|
| Scholar Experiment this skillcatlog22/maestro-flow | 564 | — | ~3.4k | Automated safety check: Notes | None | |
| Statistical Data Analysislingzhi227/agent-research-skills | 384 | — | ~886 | Automated safety check: Pass | None | |
| Q-EDA Exploratory AnalysisTyrealQ/q-skills | 108 | — | ~1.1k | Automated safety check: Pass | MIT | |
| PyMC Bayesian Modelingdavila7/claude-code-templates | 32k | 12 repos | ~3.9k | Automated safety check: Pass | MIT | |
| scikit-survival Time-to-Event Modelingdavila7/claude-code-templates | 32k | 12 repos | ~3.7k | Automated safety check: Pass | MIT | |
| Statistical Powerspacering-net/codeg | 3.8k | 2 repos | ~3.6k | Automated safety check: Notes | MIT |
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Related
Categories
Questions about Scholar Experiment
What does Scholar Experiment do?
Systematic experimental results analysis workflow for ML/AI research papers. Scholar Experiment is an agent skill from catlog22/maestro-flow. Systematic experimental results analysis workflow for ML/AI research papers.
When should I use Scholar Experiment?
Scholar Experiment fits situations like: analyze experimental results; generate results section; statistical analysis of experiments; compare model performance.
How do I install Scholar Experiment in Claude Code?
Run `npx skills add catlog22/maestro-flow --skill scholar-experiment -a claude-code`. Or copy the skill folder (optional/skills/scholar-experiment in catlog22/maestro-flow) into .claude/skills/scholar-experiment in your project. Claude Code loads it when a task matches its description.
How do I install Scholar Experiment in Codex?
Run `npx skills add catlog22/maestro-flow --skill scholar-experiment -a codex`. Or copy the skill folder (optional/skills/scholar-experiment in catlog22/maestro-flow) into .agents/skills/scholar-experiment in your project. Codex loads it when a task matches its description.
Can I use Scholar Experiment 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 catlog22/maestro-flow --skill scholar-experiment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scholar-experiment, .gemini/skills/scholar-experiment, .github/skills/scholar-experiment and .opencode/skills/scholar-experiment in your project.
What does Scholar Experiment need to run?
SKILL.md names no scripts, command-line tools or credentials: Scholar Experiment is instructions for the agent only. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep, AskUserQuestion, TodoWrite.
Does Scholar Experiment 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 Scholar Experiment safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Scholar Experiment use?
No licence was found for Scholar Experiment or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Scholar Experiment use?
About 3.4k tokens (SKILL.md is roughly 14k 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 Scholar Experiment?
Skills that share tags, products or a category with Scholar Experiment: Statistical Data Analysis (lingzhi227/agent-research-skills, 384 stars), Q-EDA Exploratory Analysis (TyrealQ/q-skills, 108 stars), PyMC Bayesian Modeling (davila7/claude-code-templates, 32k stars) and scikit-survival Time-to-Event Modeling (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Scholar Experiment?
catlog22 (a GitHub user) maintains it in catlog22/maestro-flow, which has 564 GitHub stars. The repository holds 30 skills in this directory. The repository was last updated on October 7, 2026.
Source: catlog22/maestro-flow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.