Pandas Pro
Jeffallan/claude-skills
Handles pandas DataFrame work: cleaning, merging, groupby aggregation, pivots, time-series resampling and memory tuning, with checks on dtypes, shapes and nulls.
Use outlier detection handler for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
$ npx skills add aipoch/medical-research-skills --skill outlier-detection-handler -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aipoch/medical-research-skills outlier-detection-handler --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/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Data Analysis/outlier-detection-handler' .claude/skills/outlier-detection-handler && 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 "outlier-detection-handler" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/outlier-detection-handler into .claude/skills/outlier-detection-handler/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-handler", 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/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/outlier-detection-handlerType 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 aipoch/medical-research-skills --skill outlier-detection-handler -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aipoch/medical-research-skills outlier-detection-handler --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'scientific-skills/Data Analysis/outlier-detection-handler' .agents/skills/outlier-detection-handler && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "outlier-detection-handler" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/outlier-detection-handler into .agents/skills/outlier-detection-handler/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-handler", 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 aipoch/medical-research-skills --skill outlier-detection-handler -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aipoch/medical-research-skills outlier-detection-handler --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'scientific-skills/Data Analysis/outlier-detection-handler' .cursor/skills/outlier-detection-handler && 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 "outlier-detection-handler" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/outlier-detection-handler into .cursor/skills/outlier-detection-handler/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-handler", 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/aipoch/medical-research-skills.git --path 'scientific-skills/Data Analysis/outlier-detection-handler'--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 aipoch/medical-research-skills --skill outlier-detection-handler -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aipoch/medical-research-skills outlier-detection-handler --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'scientific-skills/Data Analysis/outlier-detection-handler' .gemini/skills/outlier-detection-handler && 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 "outlier-detection-handler" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/outlier-detection-handler into .gemini/skills/outlier-detection-handler/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-handler", 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 aipoch/medical-research-skills outlier-detection-handlerInstalls 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 aipoch/medical-research-skills --skill outlier-detection-handler -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'scientific-skills/Data Analysis/outlier-detection-handler' .github/skills/outlier-detection-handler && 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 "outlier-detection-handler" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/outlier-detection-handler into .github/skills/outlier-detection-handler/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-handler", 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 aipoch/medical-research-skills --skill outlier-detection-handler -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aipoch/medical-research-skills outlier-detection-handler --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'scientific-skills/Data Analysis/outlier-detection-handler' .opencode/skills/outlier-detection-handler && 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 "outlier-detection-handler" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Data%20Analysis/outlier-detection-handler into .opencode/skills/outlier-detection-handler/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-handler", 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.
outlier-detection-handlerUse outlier detection handler for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
Outlier Detection Handler is an agent skill from aipoch/medical-research-skills. Use outlier detection handler for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `POLISH_CHANGELOG.md`, `eval_report_outlier-detection-handler_result.json` and `scripts/main.py`).
It sits in Data & Analytics, covering Data cleaning and Data analysis. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Outlier Detection Handler loads about 2k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 977 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.
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); the scripts in this folder are not scanned.
The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 977 words, ~2,029 tokens.
.claude/skills/outlier-detection-handler/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Identify and manage statistical outliers.
Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.pyUse these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
python -m py_compile scripts/main.py
python scripts/main.py --help| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
data | str | Yes | - | Path to dataset file (CSV/Excel) |
method | str | No | "3-sigma" | Detection method: "3-sigma", "IQR", or "Grubbs" |
action | str | No | "flag" | Handling action: "flag", "remove", or "winsorize" |
Input: Biomarker measurements from 200 patients Output: 5 outliers identified (2.5%), recommended action: investigate then winsorize
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
# Python dependencies
pip install -r requirements.txtEvery final response should make these items explicit when they are relevant:
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.This skill accepts requests that match the documented purpose of outlier-detection-handler and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
outlier-detection-handleronly handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Use the following fixed structure for non-trivial requests:
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.
| Field | Required | Format/Source | Example | If Missing |
|---|---|---|---|---|
| User task description | Yes | Text | Research question, writing goal, analysis objective | Stop and ask user to provide |
| Primary input material | Depends on task | Text, file path, ID, table, or literature | PMID, PDF, CSV, DOCX, keywords, etc. | Specify which material type is missing |
| Output preference | No | Text | Language, format, target journal, template | Use skill default format |
© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts) in scientific-skills/Data Analysis/outlier-detection-handler of aipoch/medical-research-skills.
Open the folder on GitHubat commit 686e09d
Outlier Detection Handler 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 |
|---|---|---|---|---|---|---|
| Outlier Detection Handler this skillaipoch/medical-research-skills | 2k | — | ~2k | Automated safety check: Pass | MIT | |
| Pandas ProJeffallan/claude-skills | 12k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Code EngineeropenJiuwen-ai/sciencediscovery | 151 | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Verified Data Analysis with pandaspipeshub-ai/pipeshub-ai | 3.8k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Data Analysisxiaoyuge886/aigc | 198 | 1 repos | ~794 | Automated safety check: Pass | MIT | |
| Math Modeling Data Cleaning and Chartsyushui2022/MathModel-Skill | 452 | 1 repos | ~1.7k | Automated safety check: Pass | MIT |
Jeffallan/claude-skills
Handles pandas DataFrame work: cleaning, merging, groupby aggregation, pivots, time-series resampling and memory tuning, with checks on dtypes, shapes and nulls.
openJiuwen-ai/sciencediscovery
A skill your agent uses when you need to write and execute Python/R code to process, transform, and analyze data, delivering reproducible computational results with complete code-level methodology…
pipeshub-ai/pipeshub-ai
Loads, cleans, aggregates and joins tabular data with pandas under a verification rule: every number reported must be one that the code actually printed.
xiaoyuge886/aigc
Perform data analysis tasks including data cleaning, statistical analysis, visualization, and insight generation.
yushui2022/MathModel-Skill
Cleans raw or scraped competition data and produces exploratory charts and a figure plan as one stage of a mathematical modeling paper workflow.
ailabs-393/ai-labs-claude-skills
This skill should be used when analyzing CSV datasets, handling missing values through intelligent imputation, and creating interactive dashboards to visualize data trends.
aipoch/medical-research-skills
Complete workflow for generating academic research posters from PDF literature; use when you need to extract paper content from PDFs and produce a LaTeX-based poster…
aipoch/medical-research-skills
Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool.
aipoch/medical-research-skills
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.
aipoch/medical-research-skills
A toolkit for preparing ISO 13485:2016 certification documentation for medical device QMS.
aipoch/medical-research-skills
Recommends target journals for manuscript submission by analyzing the paper topic/abstract and the journal distribution of similar PubMed literature; use when users ask for journal…
aipoch/medical-research-skills
Creates academic-poster writing packages for LaTeX using beamerposter, tikzposter, or baposter.
Categories
Use outlier detection handler for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries. Outlier Detection Handler is an agent skill from aipoch/medical-research-skills. Use outlier detection handler for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
Outlier Detection Handler fits situations like: tasks that involve Data cleaning; tasks that involve Data analysis.
Run `npx skills add aipoch/medical-research-skills --skill outlier-detection-handler -a claude-code`. Or copy the skill folder (scientific-skills/Data Analysis/outlier-detection-handler in aipoch/medical-research-skills) into .claude/skills/outlier-detection-handler in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aipoch/medical-research-skills --skill outlier-detection-handler -a codex`. Or copy the skill folder (scientific-skills/Data Analysis/outlier-detection-handler in aipoch/medical-research-skills) into .agents/skills/outlier-detection-handler in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill outlier-detection-handler -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/outlier-detection-handler, .gemini/skills/outlier-detection-handler, .github/skills/outlier-detection-handler and .opencode/skills/outlier-detection-handler in your project.
Going by SKILL.md and its folder, Outlier Detection Handler needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
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.
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Outlier Detection Handler is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Outlier Detection Handler: Pandas Pro (Jeffallan/claude-skills, 12k stars), Code Engineer (openJiuwen-ai/sciencediscovery, 151 stars), Verified Data Analysis with pandas (pipeshub-ai/pipeshub-ai, 3.8k stars) and Data Analysis (xiaoyuge886/aigc, 198 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.
Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.