A skill your agent uses when writing a medical or health news story — clinical research breakthroughs, public health alerts, drug approvals, epidemiology, health policy, patient stories, risk…

MITAuto-check passedWriting & Content

Install Med Health

skills CLI
$ npx skills add asgard-ai-platform/skills --skill med-health -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install asgard-ai-platform/skills med-health --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/med-health .claude/skills/med-health && rm -rf skills-src

Use ~/.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/

Facts

Skill name
med-health
GitHub stars
242
Token cost
~3.8k tokens
SKILL.md length
1,532 words
Files
8 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when writing a medical or health news story — clinical research breakthroughs, public health alerts, drug approvals, epidemiology, health policy, patient stories, risk…

  • Works in 5 steps: Defer general workflow to… → Classify the health-story sub-type → Source vetting & evidence-hierarchy… → …
  • Writing a medical
  • SKILL.md covers Overview, When to Use, Methodology and Output Format, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Med Health is an agent skill from asgard-ai-platform/skills. Use when writing a medical or health news story — clinical research breakthroughs, public health alerts, drug approvals, epidemiology, health policy, patient stories, risk communication — from research papers, press releases, health authority statements, or interviews. Specializes the med-news-reporter workflow for health-beat discipline: relative risk framing, absolute baseline inclusion, evidence-hierarchy verification, deidentification protocol, and WHO suicide-reporting compliance. Triggers on phrases like…

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `examples/sample_input.md`, `examples/sample_output.md` and `references/ethics_and_law.md`).

It sits in Writing & Content, covering Copywriting and Clinical and healthcare research. The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • Writing a medical
  • Health news story — clinical research breakthroughs
  • Public health alerts
  • Patient stories

Example prompts

  • “寫一篇醫學新研究”
  • “draft a health news piece”
  • “整理流行病新聞”
  • “/med-health”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Defer general workflow to med-news-reporter
  2. Classify the health-story sub-type
  3. Source vetting & evidence-hierarchy tagging
  4. Health-specific risk check
  5. Evidence Hierarchy & Risk Framing Audit (health-specific addition)

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. 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 (its code samples are markdown).

    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

Med Health loads about 3.8k tokens when it runs, and up to ~14k if it reads all its reference files. Until then it costs about 209 tokens; SKILL.md has 1,532 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~209
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~14k

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 asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 1,532 words, ~3,814 tokens.

Download SKILL.mdSave it as .claude/skills/med-health/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
med-health
description
Use when writing a medical or health news story — clinical research breakthroughs, public health alerts, drug approvals, epidemiology, health policy, patient stories, risk communication — from research papers, press releases, health authority statements, or interviews. Specializes the med-news-reporter workflow for health-beat discipline: relative risk framing, absolute baseline inclusion, evidence-hierarchy verification, deidentification protocol, and WHO suicide-reporting compliance. Triggers on phrases like '寫一篇醫學新研究', 'draft a health news piece', '整理流行病新聞', '幫我把這份臨床試驗結果寫成新聞', '健康新聞報導', 'write up this drug approval', 'health story from this study'. Do NOT use for medical advice (→ consult healthcare provider), pharmaceutical marketing (→ mkt-pharma), hospital PR/press release in house voice (→ pr-press-release).
metadata.category
WP-50 大眾傳播
metadata.tags
news, journalism, health-news, medical-journalism, public-health, epidemiology, media-ethics

Medical & Health News Reporting

This skill specializes med-news-reporter for the medical/health beat. Read med-news-reporter first for the general 6-step workflow (type selection, material audit, fact-check, balance, ethics, literacy). This file adds health-specific discipline on top.

Overview

Distilled from health-journalism curricula at Stanford Medicine+Muse, Johns Hopkins SFDH, AHCJ (Association of Health Care Journalists), Columbia Mailman, NTU Public Health, and Taiwan health-media ethics standards. Covers five sub-types: research breakthroughs / public-health alerts / drug approval / health policy / patient stories. Core challenge: translating statistical evidence for public understanding without misrepresenting risk or false certainty.

IRON LAW: Relative Risk Without Absolute Risk Is Misleading

Every medical claim in the form "X% increase/decrease in risk" MUST cite
absolute baseline numbers: baseline incidence, NNT (Number Needed to Treat),
absolute risk reduction, or absolute risk change. "50% reduction in risk of
heart attack" is meaningless without "from 4 in 1000 to 2 in 1000 per year".
LLM default: lead with the relative risk (sounds dramatic), omit baseline.
Readers then overestimate the clinical significance. Override that default
by naming the denominator first, then the percentage.

Why this is non-obvious: "50% reduction" sounds much more impactful than "2 fewer heart attacks per 1000 per year", yet both describe the same result. Research-to-media translation routinely inverts this — the press release says "50% reduction", the outlet runs that number, and readers assume a larger clinical effect than evidence supports. This is the single most common source of health-news overclaim.

Rationalization Table — these justifications DO NOT override the Iron Law:

Claude might think...Why it's still a violation
"'50% reduction' is the research result, I'll just quote it"Quoting a relative-risk figure without the absolute baseline is relaying an incomplete fact. The journal paper has the baseline; the press release usually does not. Cite both or cite neither + flag.
"The baseline is in the methods section, readers can look it up"Readers will not. The article is the only context they read. Omitting it is misleading by omission, not just incomplete.
"Adding the absolute number makes the story less dramatic"That is the point. Accuracy is not a bug. If the absolute effect is small, the reader deserves to know.
"NNT is too technical for general audiences"True, and it's also the clearest way to show clinical significance. Use NNT in a side sentence ('meaning doctors would need to treat about 500 people to prevent one case'). Not optional.
"The researcher said 'statistically significant'—that's the main story"Statistically significant ≠ clinically significant. A study of 100,000 people can show a 0.5% effect as "significant" if it's real. Report both p-value and effect size.

When to Use

Trigger conditions:

  • User supplies health/medical material — journal abstracts, clinical trial results, drug approval announcements, public health advisories, epidemiological data, health-policy statements, patient interviews — and asks for a news piece.
  • User asks for "醫學新聞", "健康新聞", "health story", "research reporting", "drug news", "epidemic coverage", "health policy piece", "clinical breakthrough".
  • User paraphrases: "寫一篇醫學新研究", "整理流行病新聞", "幫我把這份臨床試驗結果寫成新聞", "turn this NIH press release into a story", "draft a piece on this WHO alert".

Input signals:

  • Named disease, drug, treatment, researcher, institution, study name, clinical trial identifier, or epidemiological data.
  • Direct quotes from clinicians, researchers, health authorities (CDC, 衛福部, WHO, etc.).
  • Statistical claims (relative risk, incidence, prevalence, mortality, efficacy, confidence intervals).
  • Regulatory status (FDA approval, 食藥署 listing, Phase III trial completion).

When NOT to use:

  • "What do I have?" / personal medical symptom advice → direct user to healthcare provider, not journalism skill.
  • Pharmaceutical company press release in the company's own voice → use pr-press-release.
  • Hospital marketing / institutional PR ("Our Advanced Surgery Center Achieves...") → use pr-*.
  • Promotion of unproven remedy or supplement as scientific fact → refuse; suggest user consult source integrity first.

Methodology

Step 0: Defer general workflow to med-news-reporter

Read or have already loaded med-news-reporter for: material audit, fact-checking, source-strength tagging, balance principle, media-ethics check, media-literacy self-check. Do not re-implement those steps here. This file specializes Steps 1, 2, 3, and adds health-specific Step 7 (Evidence Hierarchy & Risk Framing Audit).

Step 1: Classify the health-story sub-type
Sub-typeSignalsSub-template focus
Research breakthroughJournal paper, pre-print, press release from university/NIHEvidence level check; RR + AR framing; replication status
Public health alertCDC alert, 衛福部 advisory, WHO statement, disease outbreakAbsolute numbers (cases, deaths); transmission risk; at-risk population; response guidance
Drug approvalFDA/食藥署 approval, Phase III completion, clinical trial resultsTrial design rigor; efficacy + side-effect rate; NNT; cost/access; alternative treatments
Health policyCoverage decision, vaccine recommendation, screening guideline, regulationPolicy rationale; affected population; evidence basis; expert consensus; dissenting opinion
Patient storyInterview, testimonial, case narrativeDe-identification protocol; generalizability limits; attribution; expert context

If material spans sub-types (e.g. a policy change triggered by a study), classify by the primary news driver.

Step 2: Source vetting & evidence-hierarchy tagging

Every health claim must carry evidence-level tag at first mention:

Evidence Hierarchy (strongest → weakest):
1. Meta-analysis / systematic review of RCTs
2. Large RCT (n > 500)
3. Small RCT (n < 500)
4. Cohort study / case-control study
5. Case series / case report
6. Expert opinion / editorials
7. Anecdote / single patient story

Bad tagging: 「新研究表示...」(which study? what strength?) Good tagging: 「今年發表在 Lancet 的一項 1,200 人隨機對照試驗表示...」or 「基於個案報告(證據等級 5)...但尚未進行人體試驗」

Source tier (extends med-news-reporter):

TierExamplesTreatment
Government health authorityCDC, 衛福部、疾管署、食藥署、WHODirect citation; highest credibility tier
Peer-reviewed journalLancet, JAMA, BMJ, Nature Medicine, 台灣醫學會期刊Always cite journal name + DOI; include publication date
Preprint / not yet peer-reviewedmedRxiv, bioRxivMust flag as "not yet peer-reviewed"; requires editor review before publication
University press releaseWithout access to actual paperTreat as Tier 2.5; verify against journal preprint / abstract
Single researcher quoteWithout published evidenceTier 4; acceptable only as "expert opinion" with explicit caveat
Pharmaceutical companyClinical trial sponsorTier 3–4; always disclose funding source; cross-verify against independent data when possible
Patient anecdoteInterview, testimonial, Facebook postTier 7; only acceptable as illustrative narrative, never as evidence
Show full SKILL.md (701 more words)Show less
Step 3: Health-specific risk check

Beyond med-news-reporter's general ethics check, add:

  1. 個人資料保護法 (PDPA) + 醫療法 §72 (Patient Privacy):

    • Patient case reports must be de-identified: age range (not exact), no named institution/hospital, no unique medical conditions that allow re-identification.
    • Example: ❌ "63-year-old Mr. Chen A treated at NTU Hospital on March 15 for liver cancer with rare genetic mutation" (re-identifiable)
    • Example: ✅ "A 60–65-year-old male with common cancer type" (anonymized)
  2. WHO Suicide Reporting Guidelines (essential, non-negotiable):

    • Do NOT name the method, location, or date of death.
    • Do NOT publish a suicide note or detailed narrative.
    • ALWAYS include helpline number(s) (1925, 安心专线, international).
    • Do use framing: "died by suicide" or "suicide" (not "committed suicide", "successful attempt").
    • Breaking this rule increases copycat risk (Werther Effect documented by WHO); this is a professional liability.
  3. 醫療廣告法 (Medical Advertising Law):

    • If a source has financial interest in the product (pharma company, researcher with stock, hospital with proprietary treatment), disclose it.
    • Do not amplify unproven claims (e.g., supplement "cure" claims without RCT evidence).
  4. 藥物名稱使用合理性:

    • Generic name preferred over brand name ("ibuprofen" not "Advil") unless brand is essential to the story.
    • New drugs: include both generic + brand on first mention; thereafter use generic.
  5. 傳染病防治法 (Communicable Disease Control Act):

    • Early epidemic numbers are often revised as data accumulates. State explicitly: "as of [date], [source] reports X cases".
    • Avoid implied causation ("after the vaccine" ≠ "caused by the vaccine"); use temporal language precisely.
Step 4: Evidence Hierarchy & Risk Framing Audit (health-specific addition)

Before output, apply:

  1. Evidence Strength Audit: for each medical claim, verify it cites the evidence level. Single case reports must not be presented as "research shows".
  2. Relative → Absolute Conversion: every claim of "X% increase/decrease" must be paired with absolute baseline (see Iron Law above).
  3. NNT / ARR / Baseline Incidence: include at least one of these metrics to ground clinical significance.
  4. Replication Status: if this is a single study, state so ("first evidence" / "needs confirmation" / "confirms earlier findings").
  5. Confidence Interval / Uncertainty: include the range, not just the point estimate. "30% to 40%" not just "35%".
  6. Funding Disclosure: if any source has financial stake in the result, disclose it early ("funded by Pharma Corp X").

Output Format

Use the med-news-reporter base format, with health-specific additions to the meta footer:

markdown
[Headline / sub-headline / body paragraphs per med-news-reporter]

---

**稿件類型**: 醫學研究報導 / 公衛警訊 / 藥品核准 / 健康政策 / 患者故事
**字數**: approx. XXX
**消息來源層級**: 政府公衛機構 N / 同儕評審期刊 N / 預印本 N / 企業新聞稿 N / 專家意見 N / 患者訪談 N
**醫學證據稽核**:
- 每項醫學宣稱之證據等級: ✅ / ⚠️ (列出未標的)
- 相對風險 + 絕對風險配對: ✅ / ⚠️ (列出缺項: RR 未伴絕對值、NNT、基礎風險)
- 單一研究 vs 系統性評論: ✅ / N/A / ⚠️
- 95% CI / 不確定性表述: ✅ / ⚠️ (列出未含的宣稱)
**患者隱私檢核**:
- 去識別化: ✅ / ⚠️ (列出仍可追蹤身份的資訊)
- 同意書揭露: ✅ / N/A / ⚠️
**WHO 自殺守則**:
- 適用: N/A / ✅ (已遵守) / ❌ (違反項目)
**利益衝突揭露**:
- 資金來源: ✅ / N/A / ⚠️ (列出未揭露的利益相關)
**待查證事項**: ...
**倫理 / 識讀檢核摘要**: 〔交給 med-news-reporter 的 Step 4-5 footer〕

Examples

See examples/ directory for:

  • sample_input.md — realistic health-news source material (clinical study press release + health authority statement + medical society response + patient anecdote)
  • sample_output.md — produced piece + meta footer + skill-trace explanation

Gotchas

  • WHO 自殺報導守則不可選擇遵守: 不報導方法、地點、遺書;必附求助專線(1925);違反導致 copycat 效應(Werther Effect)之文件風險。這是法律 + 倫理 + 公衛的三重義務,不是新聞美學選擇。
  • 絕對風險不伴相對風險才是報導失敗: 「某藥物將 X 病死亡風險降低 50%」若不說明基礎風險(例如 1000 人中 4 人 → 2 人),讀者高估臨床意義。必須兩項並列,或都不列。
  • 預印本 (preprint) 是非同儕評審版本: medRxiv / bioRxiv 的論文尚未經 peer review,在描述時必須明確標註「未經同儕評審」。發稿前應檢驗是否已正式發表在期刊。
  • 單一研究 ≠ 醫學共識: 即使 Lancet 刊登,一篇論文不足以宣稱「科學證明」。需meta-analysis / 多中心驗證或醫學會聲明。LLM 傾向誇大單一研究的通用性。
  • NNT 的臨床意義直覺優於百分比: 「需治療 500 人才有 1 人受益」 vs 「療效提升 0.2%」——同一結果,直觀度差異極大。優先用 NNT;若無法計算則注明。
  • 製藥/醫療機構資助須在引述時點明: 研究由廠商贊助、醫師兼任產業顧問、醫院銷售新技術——這些利益衝突不揭露等同隱瞞。放在第一次引述該來源時,不要藏在尾註。
  • 患者故事去識別化不等於「模糊化」: 「一名 60 歲男性患者 A」≠ 「患者 X 是成功病例」;前者遵守個資法 §72,後者若細節足夠仍可追蹤(就醫時間+地點+罕見疾病組合)。審核時逐項檢驗。
  • 疫情数据更新快,引用需註明日期: 「確診人數 X」不標明「截至 4 月 29 日」會在重新整理後過時或誤導。時間戳必要。
  • 「治癒率」/ 「完治」/ 「成功率」各有定義: 無定冠詞引用會混淆:是 5 年存活率?完全緩解?部分緩解?必須明確定義或引用原始文件。

References

FilePurposeWhen to read
references/sources_and_beats.md台灣衛生醫療消息來源、機構、官方資料庫Step 2 source vetting
references/glossary.md醫學統計、流行病學、臨床試驗術語對照When unfamiliar medical terminology appears
references/ethics_and_law.mdPDPA / 醫療法 §72 / 醫療廣告法 / 自殺守則Step 3 risk check
references/medical_evidence_reading.md證據等級金字塔、相對風險誤導、P-hackingStep 1/4 evidence hierarchy
references/risk_communication.md風險溝通原則、絕對 vs 相對、不確定性表述Step 4 risk framing

Related skills:

  • med-news-reporter — general news workflow (this skill specializes it)
  • med-political — health policy & regulatory news
  • stat-hypothesis-testing — deeper statistical literacy on RCTs and meta-analyses
  • stat-causal-inference — for causation claims in observational studies
  • hum-source-criticism — source vetting frameworks

Limitations

  • Does not verify against live clinical trial databases or medical journals. This skill flags claims that need verification; it does not query ClinicalTrials.gov, PubMed, or Cochrane. Editor/user must verify or supply.
  • Jurisdictional scope: legal references (PDPA, 醫療法, 醫療廣告法) reflect Taiwan law. For US (HIPAA), EU (GDPR), UK, HK, or PRC contexts, principles still apply but substitution required.
  • WHO Suicide Reporting Guidelines apply globally, but enforcement and consequence differ by jurisdiction. Always apply these guidelines regardless of country of publication.
  • Statistical literacy: judges poll quality, p-hacking risk, effect-size interpretation — partially covered in references/medical_evidence_reading.md, but for deep methodological critique use stat-hypothesis-testing or grad-survey-design.
  • Not a substitute for legal review. Health-news pieces with named patients, drug/treatment criticism, or regulatory disputes should have attorney review before publication.
  • Does not generate original reporting. If supplied material is insufficient or contradictory, this skill flags gaps — it will not source additional interviews or find additional studies.

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in med-health of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_input.md
  • examples/sample_output.md
  • references/ethics_and_law.md
  • references/glossary.md
  • references/medical_evidence_reading.md
  • references/risk_communication.md
  • references/sources_and_beats.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Med Health 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.

Med Health compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Med Health this skillasgard-ai-platform/skills242—~3.8kAutomated safety check: PassMIT
Clinical Trial Analysthh-health-AI/healthcare-equity101—~849Automated safety check: PassMIT
Clinical Trial Analysthh-health-AI/healthcare-equity101—~902Automated safety check: PassMIT
Humanities Writing Companiontizzy916/humanities-writing-companion436—~3.4kAutomated safety check: PassCC-BY-NC-4.0
Biomedical Claim Checkerhh-health-AI/healthcare-equity101—~741Automated safety check: PassMIT
G2brycewang-stanford/Auto-Empirical-Research-Skills4.6k—~4.5kAutomated safety check: PassCustom licence

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Questions about Med Health

What does Med Health do?

A skill your agent uses when writing a medical or health news story — clinical research breakthroughs, public health alerts, drug approvals, epidemiology, health policy, patient stories, risk…. Med Health is an agent skill from asgard-ai-platform/skills. Use when writing a medical or health news story — clinical research breakthroughs, public health alerts, drug approvals, epidemiology, health policy, patient stories, risk communication — from research papers, press releases, health authority statements, or interviews.

When should I use Med Health?

Med Health fits situations like: writing a medical; health news story — clinical research breakthroughs; public health alerts; patient stories.

How do I install Med Health in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill med-health -a claude-code`. Or copy the skill folder (med-health in asgard-ai-platform/skills) into .claude/skills/med-health in your project. Claude Code loads it when a task matches its description.

How do I install Med Health in Codex?

Run `npx skills add asgard-ai-platform/skills --skill med-health -a codex`. Or copy the skill folder (med-health in asgard-ai-platform/skills) into .agents/skills/med-health in your project. Codex loads it when a task matches its description.

Can I use Med Health 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 asgard-ai-platform/skills --skill med-health -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/med-health, .gemini/skills/med-health, .github/skills/med-health and .opencode/skills/med-health in your project.

What does Med Health need to run?

SKILL.md names no scripts, command-line tools or credentials: Med Health is instructions for the agent only.

Does Med Health 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 Med Health 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 Med Health use?

Med Health 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 Med Health use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 10k tokens, read only when the agent opens those files.

What are the alternatives to Med Health?

Skills that share tags, products or a category with Med Health: Clinical Trial Analyst (hh-health-AI/healthcare-equity, 101 stars), Clinical Trial Analyst (hh-health-AI/healthcare-equity, 101 stars), Humanities Writing Companion (tizzy916/humanities-writing-companion, 436 stars) and Biomedical Claim Checker (hh-health-AI/healthcare-equity, 101 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Med Health?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.