Add Parser
aropan/clist
Add, fix, or debug a Django standings parser in src/ranking/management/modules/, including Statistic.getstandings, leaderboard scraping, and offline regression fixtures.
Access FDA drug data and WHO global health statistics for research
$ npx skills add wentorai/research-plugins --skill medical-data-api -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wentorai/research-plugins medical-data-api --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/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/domains/biomedical/medical-data-api .claude/skills/medical-data-api && 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 "medical-data-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/biomedical/medical-data-api into .claude/skills/medical-data-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "medical-data-api", 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/wentorai/research-plugins/tree/main/skills/domains/biomedical/medical-data-apiType 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 wentorai/research-plugins --skill medical-data-api -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wentorai/research-plugins medical-data-api --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/domains/biomedical/medical-data-api .agents/skills/medical-data-api && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "medical-data-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/biomedical/medical-data-api into .agents/skills/medical-data-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "medical-data-api", 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 wentorai/research-plugins --skill medical-data-api -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wentorai/research-plugins medical-data-api --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/domains/biomedical/medical-data-api .cursor/skills/medical-data-api && 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 "medical-data-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/biomedical/medical-data-api into .cursor/skills/medical-data-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "medical-data-api", 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/wentorai/research-plugins.git --path skills/domains/biomedical/medical-data-api--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 wentorai/research-plugins --skill medical-data-api -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wentorai/research-plugins medical-data-api --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/domains/biomedical/medical-data-api .gemini/skills/medical-data-api && 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 "medical-data-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/biomedical/medical-data-api into .gemini/skills/medical-data-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "medical-data-api", 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 wentorai/research-plugins medical-data-apiInstalls 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 wentorai/research-plugins --skill medical-data-api -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/domains/biomedical/medical-data-api .github/skills/medical-data-api && 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 "medical-data-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/biomedical/medical-data-api into .github/skills/medical-data-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "medical-data-api", 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 wentorai/research-plugins --skill medical-data-api -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wentorai/research-plugins medical-data-api --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/domains/biomedical/medical-data-api .opencode/skills/medical-data-api && 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 "medical-data-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/biomedical/medical-data-api into .opencode/skills/medical-data-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "medical-data-api", 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.
medical-data-apiAccess FDA drug data and WHO global health statistics for research
Medical Data API is an agent skill from wentorai/research-plugins. Access FDA drug data and WHO global health statistics for research
Its SKILL.md is about 2.2k 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. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.
Read from SKILL.md and the folder at commit bf44b3c. 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.
Shell commands in SKILL.md call:
curlFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
ghoapi.azureedge.netapi.fda.govAlso links to:
open.fda.govwho.intgithub.comFrom 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.
Medical Data API loads about 2.2k tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 704 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); files beside SKILL.md are not scanned.
The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 704 words, ~2,217 tokens.
.claude/skills/medical-data-api/SKILL.md (or your agent's skills folder).This skill covers two major open medical data APIs for academic research:
openFDA is the U.S. Food and Drug Administration's public API providing access to drug labeling (SPL), adverse event reports (FAERS), recalls, and NDC directory. The FAERS dataset contains over 722,000 reports for common drugs like aspirin, making it a primary pharmacovigilance resource.
WHO Global Health Observatory (GHO) is the WHO's OData v4 API serving over 2,000 health indicators across 194 member states -- life expectancy, mortality, disease burden, health system coverage, risk factors, and SDG targets. Returns structured JSON with numeric values, confidence intervals, and dimensional breakdowns by country, sex, and year.
Both APIs are free, require no authentication, and return JSON.
openFDA: No authentication required. An optional API key (free, via https://open.fda.gov/apis/authentication/) increases rate limits from 240/min to 120,000/day. Register at https://open.fda.gov/apis/ to obtain a key, then append &api_key=YOUR_KEY to requests.
WHO GHO: No authentication required. No API key needed. All endpoints are publicly accessible with no registration.
Search FDA-approved drug labeling data (Structured Product Labeling). Returns boxed warnings, indications, dosage, contraindications, and adverse reactions text.
GET https://api.fda.gov/drug/label.json| Parameter | Type | Required | Description |
|---|---|---|---|
| search | string | No | Search query using openFDA query syntax |
| limit | int | No | Number of results (default 1, max 1000) |
| skip | int | No | Offset for pagination |
| count | string | No | Count unique values of a field |
curl "https://api.fda.gov/drug/label.json?search=aspirin&limit=1"meta.results.total (26,564 for "aspirin") and results array. Each result contains boxed_warning, indications_and_usage, dosage_and_administration, warnings, adverse_reactions, drug_interactions, and openfda cross-references (brand/generic names, manufacturer, NDC, pharmacologic class).Search the FDA Adverse Event Reporting System. Each record describes a safety report including patient demographics, suspect drugs, reported reactions, and outcomes.
GET https://api.fda.gov/drug/event.json| Parameter | Type | Required | Description |
|---|---|---|---|
| search | string | No | Query (e.g., patient.drug.openfda.brand_name:"aspirin") |
| limit | int | No | Number of results (default 1, max 1000) |
| skip | int | No | Offset for pagination (max skip+limit = 26,000) |
| count | string | No | Count field values (e.g., patient.reaction.reactionmeddrapt.exact) |
curl 'https://api.fda.gov/drug/event.json?search=patient.drug.openfda.brand_name:"aspirin"&limit=1'meta.results.total (722,607 for aspirin). Each result: safetyreportid, serious (1=yes, 2=no), primarysourcecountry, receivedate, nested patient with patientsex, reaction array (MedDRA terms + reactionoutcome), and drug array with drugcharacterization (1=suspect, 2=concomitant, 3=interacting), medicinalproduct, openfda cross-references.Retrieve data points for a specific health indicator with country, year, and sex dimensions.
GET https://ghoapi.azureedge.net/api/{IndicatorCode}| Parameter | Type | Required | Description |
|---|---|---|---|
| $top | int | No | Limit number of records returned |
| $skip | int | No | Skip records for pagination |
| $filter | string | No | OData filter (e.g., SpatialDim eq 'USA' and TimeDim eq 2020) |
| $select | string | No | Select specific fields |
| $orderby | string | No | Sort results |
# Life expectancy at birth (WHOSIS_000001)
curl "https://ghoapi.azureedge.net/api/WHOSIS_000001?\$top=2"value array. Each record: SpatialDim (ISO country, e.g., "BTN"), ParentLocation (WHO region), TimeDim (year), Dim1 (sex: "SEX_BTSX"/"SEX_MLE"/"SEX_FMLE"), Value ("67.8 [67.1-68.6]"), NumericValue (67.845665), Low/High confidence bounds.List available health indicators with their codes and names.
GET https://ghoapi.azureedge.net/api/Indicatorcurl "https://ghoapi.azureedge.net/api/Indicator?\$top=5"IndicatorCode (e.g., "Adult_curr_e-cig"), IndicatorName (e.g., "Prevalence of current e-cigarette use among adults (%)"), Language ("EN"). Over 2,000 indicators spanning mortality, morbidity, health systems, and risk factors.openFDA:
skip + limit cannot exceed 26,000 (use search + sort for deeper access)WHO GHO:
Count reactions by MedDRA term to identify safety signals:
import requests
resp = requests.get("https://api.fda.gov/drug/event.json", params={
"search": 'patient.drug.openfda.brand_name:"aspirin"',
"count": "patient.reaction.reactionmeddrapt.exact",
"limit": 10
})
for r in resp.json()["results"]:
print(f" {r['term']}: {r['count']} reports")Compare health indicators across countries and time periods:
import requests
resp = requests.get("https://ghoapi.azureedge.net/api/WHOSIS_000001", params={
"$filter": "SpatialDim eq 'JPN' and Dim1 eq 'SEX_BTSX'",
"$orderby": "TimeDim desc",
"$top": 10
})
for row in resp.json()["value"]:
print(f" Japan {row['TimeDim']}: {row['Value']}")Compare safety language across drug labels for regulatory research:
import requests
for drug in ["ibuprofen", "naproxen", "celecoxib"]:
resp = requests.get("https://api.fda.gov/drug/label.json",
params={"search": f'openfda.generic_name:"{drug}"', "limit": 1})
results = resp.json().get("results", [])
if results:
warning = results[0].get("boxed_warning", ["None"])[0][:200]
print(f"{drug.upper()}: {warning}...\n")| Code | Indicator |
|---|---|
| WHOSIS_000001 | Life expectancy at birth |
| NCDMORT3070 | NCD mortality (30-70 years) |
| MDG_0000000001 | Under-five mortality rate |
| WHS4_100 | Physicians per 10,000 population |
| NCD_BMI_30A | Prevalence of obesity (BMI >= 30) |
| SA_0000001688 | Alcohol per capita consumption |
| TOBACCO_0000000262 | Tobacco smoking prevalence |
© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/domains/biomedical/medical-data-api of wentorai/research-plugins.
Open the folder on GitHubat commit bf44b3c
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.
Medical Data API 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 |
|---|---|---|---|---|---|---|
| Medical Data API this skillwentorai/research-plugins | 298 | 1 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Add Parseraropan/clist | 439 | — | ~812 | Automated safety check: Pass | Apache-2.0 | |
| Analyzing API Gateway Access Logsmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~581 | Automated safety check: Pass | Apache-2.0 | |
| Sandbox Benchvercel/next.js | 143k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Statistical Analysisspacering-net/codeg | 3.9k | 3 repos | ~5k | Automated safety check: Pass | MIT | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause |
aropan/clist
Add, fix, or debug a Django standings parser in src/ranking/management/modules/, including Statistic.getstandings, leaderboard scraping, and offline regression fixtures.
mukul975/Anthropic-Cybersecurity-Skills
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts.
vercel/next.js
Benchmark React or Next.js changes on Vercel Sandbox VMs with paired A/B statistics: react PR/commit vs base, or Next.js PR/commit vs base, measured end-to-end through the bench/render-pipeline app…
spacering-net/codeg
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting.
zLanqing/codex-claude-academic-skills
Statistical models library for Python. An agent skill from zLanqing/codex-claude-academic-skills.
vigorX777/ai-daily-digest
Fetches RSS feeds from 90 top Hacker News blogs (curated by Karpathy), uses AI to score and filter articles, and generates a daily digest in Markdown with Chinese-translated titles, category…
wentorai/research-plugins
Craft structured research abstracts that maximize clarity and journal acceptance
wentorai/research-plugins
Manage academic citations across BibTeX, APA, MLA, and Chicago formats
wentorai/research-plugins
Summarize academic papers with structured extraction of key elements
wentorai/research-plugins
Evidence-based study techniques for academic learning and retention
wentorai/research-plugins
Adjust writing tone and register for academic audiences and venues
wentorai/research-plugins
Academic translation, post-editing, and Chinglish correction guide
Categories
Access FDA drug data and WHO global health statistics for research. Medical Data API is an agent skill from wentorai/research-plugins.
Medical Data API fits situations like: tasks that involve Statistics.
Run `npx skills add wentorai/research-plugins --skill medical-data-api -a claude-code`. Or copy the skill folder (skills/domains/biomedical/medical-data-api in wentorai/research-plugins) into .claude/skills/medical-data-api in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wentorai/research-plugins --skill medical-data-api -a codex`. Or copy the skill folder (skills/domains/biomedical/medical-data-api in wentorai/research-plugins) into .agents/skills/medical-data-api 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 wentorai/research-plugins --skill medical-data-api -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/medical-data-api, .gemini/skills/medical-data-api, .github/skills/medical-data-api and .opencode/skills/medical-data-api in your project.
Going by SKILL.md and its folder, Medical Data API needs the command-line tools its instructions call (curl). Our summary lists: Python 3; A credential in YOUR_KEY.
SKILL.md names 5 domains. In commands or code: ghoapi.azureedge.net and api.fda.gov; the agent is likely to contact these when it follows the instructions. As links in the text: open.fda.gov, who.int and github.com. 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. Review the folder before installing.
Medical Data API is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.2k tokens (SKILL.md is roughly 8.9k 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 Medical Data API: Add Parser (aropan/clist, 439 stars), Analyzing API Gateway Access Logs (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Sandbox Bench (vercel/next.js, 143k stars) and Statistical Analysis (spacering-net/codeg, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.
Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.