Gnomad Database
jaechang-hits/SciAgent-Skills
gnomAD v4 population variant frequencies via GraphQL API. An agent skill from jaechang-hits/SciAgent-Skills.
Query gnomAD (Genome Aggregation Database) for population allele frequencies, variant constraint scores (pLI, LOEUF), and loss-of-function intolerance.
$ npx skills add LeonChaoX/qinyan-academic-skills --skill gnomad-database -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeonChaoX/qinyan-academic-skills gnomad-database --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/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'skills/12-科学数据库/gnomad-database' .claude/skills/gnomad-database && 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 "gnomad-database" agent skill from https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/gnomad-database into .claude/skills/gnomad-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gnomad-database", 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/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/gnomad-databaseType 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 LeonChaoX/qinyan-academic-skills --skill gnomad-database -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeonChaoX/qinyan-academic-skills gnomad-database --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'skills/12-科学数据库/gnomad-database' .agents/skills/gnomad-database && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "gnomad-database" agent skill from https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/gnomad-database into .agents/skills/gnomad-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gnomad-database", 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 LeonChaoX/qinyan-academic-skills --skill gnomad-database -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeonChaoX/qinyan-academic-skills gnomad-database --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'skills/12-科学数据库/gnomad-database' .cursor/skills/gnomad-database && 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 "gnomad-database" agent skill from https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/gnomad-database into .cursor/skills/gnomad-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gnomad-database", 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/LeonChaoX/qinyan-academic-skills.git --path 'skills/12-科学数据库/gnomad-database'--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 LeonChaoX/qinyan-academic-skills --skill gnomad-database -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeonChaoX/qinyan-academic-skills gnomad-database --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'skills/12-科学数据库/gnomad-database' .gemini/skills/gnomad-database && 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 "gnomad-database" agent skill from https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/gnomad-database into .gemini/skills/gnomad-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gnomad-database", 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 LeonChaoX/qinyan-academic-skills gnomad-databaseInstalls 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 LeonChaoX/qinyan-academic-skills --skill gnomad-database -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'skills/12-科学数据库/gnomad-database' .github/skills/gnomad-database && 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 "gnomad-database" agent skill from https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/gnomad-database into .github/skills/gnomad-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gnomad-database", 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 LeonChaoX/qinyan-academic-skills --skill gnomad-database -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeonChaoX/qinyan-academic-skills gnomad-database --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'skills/12-科学数据库/gnomad-database' .opencode/skills/gnomad-database && 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 "gnomad-database" agent skill from https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/gnomad-database into .opencode/skills/gnomad-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gnomad-database", 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.
gnomad-databaseQuery gnomAD (Genome Aggregation Database) for population allele frequencies, variant constraint scores (pLI, LOEUF), and loss-of-function intolerance.
Gnomad Database is an agent skill from LeonChaoX/qinyan-academic-skills. Query gnomAD (Genome Aggregation Database) for population allele frequencies, variant constraint scores (pLI, LOEUF), and loss-of-function intolerance. Essential for variant pathogenicity interpretation, rare disease genetics, and identifying loss-of-function intolerant genes.
Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/graphql_queries.md` and `references/variant_interpretation.md`).
It sits in Research & Science, covering Bioinformatics. It works with GraphQL. The repository describes itself as: A curated, multilingual library of 182 installable AI agent skills for end-to-end academic research—spanning literature discovery, scientific writing, grant development… The licence is CC0-1.0.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit df5a498. 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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From 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:
gnomad.broadinstitute.orgAlso links to:
github.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.
Gnomad Database loads about 3.1k tokens when it runs, and up to ~5.3k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 639 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 LeonChaoX/qinyan-academic-skills at commit df5a498, republished under its CC0-1.0 licence (© LeonChaoX). 639 words, ~3,114 tokens.
.claude/skills/gnomad-database/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.The Genome Aggregation Database (gnomAD) is the largest publicly available collection of human genetic variation, aggregated from large-scale sequencing projects. gnomAD v4 contains exome sequences from 730,947 individuals and genome sequences from 76,215 individuals across diverse ancestries. It provides population allele frequencies, variant consequence annotations, and gene-level constraint metrics that are essential for interpreting the clinical significance of genetic variants.
Key resources:
Use gnomAD when:
gnomAD uses a GraphQL API accessible at https://gnomad.broadinstitute.org/api. Most queries fetch variants by gene or specific genomic position.
Datasets available:
gnomad_r4 — gnomAD v4 exomes (recommended default, GRCh38)gnomad_r4_genomes — gnomAD v4 genomes (GRCh38)gnomad_r3 — gnomAD v3 genomes (GRCh38)gnomad_r2_1 — gnomAD v2 exomes (GRCh37)Reference genomes:
GRCh38 — default for v3/v4GRCh37 — for v2import requests
def query_gnomad_gene(gene_symbol, dataset="gnomad_r4", reference_genome="GRCh38"):
"""Fetch variants in a gene from gnomAD."""
url = "https://gnomad.broadinstitute.org/api"
query = """
query GeneVariants($gene_symbol: String!, $dataset: DatasetId!, $reference_genome: ReferenceGenomeId!) {
gene(gene_symbol: $gene_symbol, reference_genome: $reference_genome) {
gene_id
gene_symbol
variants(dataset: $dataset) {
variant_id
pos
ref
alt
consequence
genome {
af
ac
an
ac_hom
populations {
id
ac
an
af
}
}
exome {
af
ac
an
ac_hom
}
lof
lof_flags
lof_filter
}
}
}
"""
variables = {
"gene_symbol": gene_symbol,
"dataset": dataset,
"reference_genome": reference_genome
}
response = requests.post(url, json={"query": query, "variables": variables})
return response.json()
# Example
result = query_gnomad_gene("BRCA1")
gene_data = result["data"]["gene"]
variants = gene_data["variants"]
# Filter to rare PTVs
rare_ptvs = [
v for v in variants
if v.get("lof") == "LC" or v.get("consequence") in ["stop_gained", "frameshift_variant"]
and v.get("genome", {}).get("af", 1) < 0.001
]
print(f"Found {len(rare_ptvs)} rare PTVs in {gene_data['gene_symbol']}")import requests
def query_gnomad_variant(variant_id, dataset="gnomad_r4"):
"""Fetch details for a specific variant (e.g., '1-55516888-G-GA')."""
url = "https://gnomad.broadinstitute.org/api"
query = """
query VariantDetails($variantId: String!, $dataset: DatasetId!) {
variant(variantId: $variantId, dataset: $dataset) {
variant_id
chrom
pos
ref
alt
genome {
af
ac
an
ac_hom
populations {
id
ac
an
af
}
}
exome {
af
ac
an
ac_hom
populations {
id
ac
an
af
}
}
consequence
lof
rsids
in_silico_predictors {
id
value
flags
}
clinvar_variation_id
}
}
"""
response = requests.post(
url,
json={"query": query, "variables": {"variantId": variant_id, "dataset": dataset}}
)
return response.json()
# Example: query a specific variant
result = query_gnomad_variant("17-43094692-G-A") # BRCA1 missense
variant = result["data"]["variant"]
if variant:
genome_af = variant.get("genome", {}).get("af", "N/A")
exome_af = variant.get("exome", {}).get("af", "N/A")
print(f"Variant: {variant['variant_id']}")
print(f" Consequence: {variant['consequence']}")
print(f" Genome AF: {genome_af}")
print(f" Exome AF: {exome_af}")
print(f" LoF: {variant.get('lof')}")gnomAD constraint scores assess how tolerant a gene is to variation relative to expectation:
import requests
def query_gnomad_constraint(gene_symbol, reference_genome="GRCh38"):
"""Fetch constraint scores for a gene."""
url = "https://gnomad.broadinstitute.org/api"
query = """
query GeneConstraint($gene_symbol: String!, $reference_genome: ReferenceGenomeId!) {
gene(gene_symbol: $gene_symbol, reference_genome: $reference_genome) {
gene_id
gene_symbol
gnomad_constraint {
exp_lof
exp_mis
exp_syn
obs_lof
obs_mis
obs_syn
oe_lof
oe_mis
oe_syn
oe_lof_lower
oe_lof_upper
lof_z
mis_z
syn_z
pLI
}
}
}
"""
response = requests.post(
url,
json={"query": query, "variables": {"gene_symbol": gene_symbol, "reference_genome": reference_genome}}
)
return response.json()
# Example
result = query_gnomad_constraint("KCNQ2")
gene = result["data"]["gene"]
constraint = gene["gnomad_constraint"]
print(f"Gene: {gene['gene_symbol']}")
print(f" pLI: {constraint['pLI']:.3f} (>0.9 = LoF intolerant)")
print(f" LOEUF: {constraint['oe_lof_upper']:.3f} (<0.35 = highly constrained)")
print(f" Obs/Exp LoF: {constraint['oe_lof']:.3f}")
print(f" Missense Z: {constraint['mis_z']:.3f}")Constraint score interpretation:
| Score | Range | Meaning |
|---|---|---|
pLI | 0–1 | Probability of LoF intolerance; >0.9 = highly intolerant |
LOEUF | 0–∞ | LoF observed/expected upper bound; <0.35 = constrained |
oe_lof | 0–∞ | Observed/expected ratio for LoF variants |
mis_z | −∞ to ∞ | Missense constraint z-score; >3.09 = constrained |
syn_z | −∞ to ∞ | Synonymous z-score (control; should be near 0) |
import requests
import pandas as pd
def get_population_frequencies(variant_id, dataset="gnomad_r4"):
"""Extract per-population allele frequencies for a variant."""
url = "https://gnomad.broadinstitute.org/api"
query = """
query PopFreqs($variantId: String!, $dataset: DatasetId!) {
variant(variantId: $variantId, dataset: $dataset) {
variant_id
genome {
populations {
id
ac
an
af
ac_hom
}
}
}
}
"""
response = requests.post(
url,
json={"query": query, "variables": {"variantId": variant_id, "dataset": dataset}}
)
data = response.json()
populations = data["data"]["variant"]["genome"]["populations"]
df = pd.DataFrame(populations)
df = df[df["an"] > 0].copy()
df["af"] = df["ac"] / df["an"]
df = df.sort_values("af", ascending=False)
return df
# Population IDs in gnomAD v4:
# afr = African/African American
# ami = Amish
# amr = Admixed American
# asj = Ashkenazi Jewish
# eas = East Asian
# fin = Finnish
# mid = Middle Eastern
# nfe = Non-Finnish European
# sas = South Asian
# remaining = OthergnomAD also contains a structural variant dataset:
import requests
def query_gnomad_sv(gene_symbol):
"""Query structural variants overlapping a gene."""
url = "https://gnomad.broadinstitute.org/api"
query = """
query SVsByGene($gene_symbol: String!) {
gene(gene_symbol: $gene_symbol, reference_genome: GRCh38) {
structural_variants {
variant_id
type
chrom
pos
end
af
ac
an
}
}
}
"""
response = requests.post(url, json={"query": query, "variables": {"gene_symbol": gene_symbol}})
return response.json()Check population frequency — Is the variant rare enough to be pathogenic?
Assess functional impact — LoF variants have highest prior probability
lof field: HC = high-confidence LoF, LC = low-confidencelof_flags for issues like "NAGNAG_SITE", "PHYLOCSF_WEAK"Apply ACMG criteria:
ac_hom) are relevant for recessive disease analysis© LeonChaoX, CC0-1.0. 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 2 other files (references) in skills/12-科学数据库/gnomad-database of LeonChaoX/qinyan-academic-skills.
Open the folder on GitHubat commit df5a498
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 LeonChaoX/qinyan-academic-skills, which our catalogue first saw on October 9, 2026.
Gnomad Database 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 |
|---|---|---|---|---|---|---|
| Gnomad Database this skillLeonChaoX/qinyan-academic-skills | 943 | 1 repos | ~3.1k | Automated safety check: Pass | CC0-1.0 | |
| Gnomad Databasejaechang-hits/SciAgent-Skills | 371 | 1 repos | ~7.2k | Automated safety check: Pass | Custom licence | |
| Alphagenome Single Variant Analysisgoogle-deepmind/science-skills | 3.2k | 2 repos | ~3k | Automated safety check: Notes | Apache-2.0 | |
| 13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Clinvar Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Metabolic Study Planneraiming-lab/AutoResearchClaw | 15k | — | ~1.9k | Automated safety check: Pass | MIT |
jaechang-hits/SciAgent-Skills
gnomAD v4 population variant frequencies via GraphQL API. An agent skill from jaechang-hits/SciAgent-Skills.
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
K-Dense-AI/scientific-agent-skills
Estimates reaction fluxes inside cells from steady-state carbon-13 labeling data with a bundled mfapy-based solver, and reports which fluxes the data pin down.
google-deepmind/science-skills
A skill your agent uses when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls…
aiming-lab/AutoResearchClaw
Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.
google-deepmind/science-skills
A skill your agent uses when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database.
LeonChaoX/qinyan-academic-skills
Generate professional slide deck images from academic papers and content.
LeonChaoX/qinyan-academic-skills
Search the web, extract URL content, and run deep research using the Parallel Chat API and Extract API.
LeonChaoX/qinyan-academic-skills
Generate academic research proposals for PhD applications. An agent skill from LeonChaoX/qinyan-academic-skills.
LeonChaoX/qinyan-academic-skills
Write comprehensive literature reviews for medical imaging AI research.
LeonChaoX/qinyan-academic-skills
Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles.
LeonChaoX/qinyan-academic-skills
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML).
Works with
Categories
Query gnomAD (Genome Aggregation Database) for population allele frequencies, variant constraint scores (pLI, LOEUF), and loss-of-function intolerance. Gnomad Database is an agent skill from LeonChaoX/qinyan-academic-skills. Query gnomAD (Genome Aggregation Database) for population allele frequencies, variant constraint scores (pLI, LOEUF), and loss-of-function intolerance.
Gnomad Database fits situations like: tasks that involve Bioinformatics.
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill gnomad-database -a claude-code`. Or copy the skill folder (skills/12-科学数据库/gnomad-database in LeonChaoX/qinyan-academic-skills) into .claude/skills/gnomad-database in your project. Claude Code loads it when a task matches its description.
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill gnomad-database -a codex`. Or copy the skill folder (skills/12-科学数据库/gnomad-database in LeonChaoX/qinyan-academic-skills) into .agents/skills/gnomad-database 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 LeonChaoX/qinyan-academic-skills --skill gnomad-database -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gnomad-database, .gemini/skills/gnomad-database, .github/skills/gnomad-database and .opencode/skills/gnomad-database in your project.
SKILL.md names no scripts, command-line tools or credentials: Gnomad Database is instructions for the agent only. Our summary lists: Python 3.
SKILL.md names 2 domains. In commands or code: gnomad.broadinstitute.org; the agent is likely to contact it when it follows the instructions. As links in the text: 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.
Gnomad Database is published under the CC0-1.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.1k tokens (SKILL.md is roughly 12k 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 2.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Gnomad Database: Gnomad Database (jaechang-hits/SciAgent-Skills, 371 stars), Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars) and Clinvar Database (google-deepmind/science-skills, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
LeonChaoX (a GitHub user) maintains it in LeonChaoX/qinyan-academic-skills, which has 943 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeonChaoX/qinyan-academic-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.