tangermeme Genomic Model Analysis
jmschrei/tangermeme
Routes agents to the right tangermeme reference for analyzing trained genomic deep learning models, from attributions and motif experiments to variant effects and design.
Calls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and…
$ npx skills add GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-clair3-variants --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/GPTomics/bioSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/long-read-sequencing/clair3-variants .claude/skills/bio-long-read-sequencing-clair3-variants && 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 "bio-long-read-sequencing-clair3-variants" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/clair3-variants into .claude/skills/bio-long-read-sequencing-clair3-variants/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-clair3-variants", 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/GPTomics/bioSkills/tree/main/long-read-sequencing/clair3-variantsType 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 GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-clair3-variants --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/long-read-sequencing/clair3-variants .agents/skills/bio-long-read-sequencing-clair3-variants && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bio-long-read-sequencing-clair3-variants" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/clair3-variants into .agents/skills/bio-long-read-sequencing-clair3-variants/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-clair3-variants", 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 GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-clair3-variants --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/long-read-sequencing/clair3-variants .cursor/skills/bio-long-read-sequencing-clair3-variants && 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 "bio-long-read-sequencing-clair3-variants" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/clair3-variants into .cursor/skills/bio-long-read-sequencing-clair3-variants/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-clair3-variants", 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/GPTomics/bioSkills.git --path long-read-sequencing/clair3-variants--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 GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-clair3-variants --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/long-read-sequencing/clair3-variants .gemini/skills/bio-long-read-sequencing-clair3-variants && 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 "bio-long-read-sequencing-clair3-variants" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/clair3-variants into .gemini/skills/bio-long-read-sequencing-clair3-variants/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-clair3-variants", 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 GPTomics/bioSkills bio-long-read-sequencing-clair3-variantsInstalls 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 GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .github/skills && cp -r skills-src/long-read-sequencing/clair3-variants .github/skills/bio-long-read-sequencing-clair3-variants && 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 "bio-long-read-sequencing-clair3-variants" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/clair3-variants into .github/skills/bio-long-read-sequencing-clair3-variants/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-clair3-variants", 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 GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-clair3-variants --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/long-read-sequencing/clair3-variants .opencode/skills/bio-long-read-sequencing-clair3-variants && 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 "bio-long-read-sequencing-clair3-variants" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/clair3-variants into .opencode/skills/bio-long-read-sequencing-clair3-variants/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-clair3-variants", 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.
bio-long-read-sequencing-clair3-variantsCalls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and…
Bio Long Read Sequencing Clair3 Variants is an agent skill from GPTomics/bioSkills. Calls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and basecaller-version-matched model, enabling read-based phasing, and benchmarking against GIAB with stratification. Covers why the model string is the experiment (no auto-detection, silent degradation on mismatch), why ONT homopolymer/STR indels are the residual error whole-genome F1 hides, and the somatic/trio/RNA…
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `examples/clair3_workflow.sh` and `usage-guide.md`).
It sits in Research & Science, covering Bioinformatics and Deep learning. The repository describes itself as: a set of SKILLS.md for doing bioinformatics with agents like claude code. The licence is MIT.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit d91ed3d. 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 script files (Shell), which the agent can run.
From 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.
Bio Long Read Sequencing Clair3 Variants loads about 2.9k tokens when it runs. Until then it costs about 183 tokens; SKILL.md has 1,198 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 GPTomics/bioSkills at commit d91ed3d, republished under its MIT licence (© GPTomics). 1,198 words, ~2,899 tokens.
.claude/skills/bio-long-read-sequencing-clair3-variants/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Reference examples tested with: Clair3 2.0+, whatshap 2.0+, bcftools 1.19+, hap.py 0.3.15+.
Before using code patterns, verify installed versions match. If versions differ:
<tool> --version then <tool> --help to confirm flagsResults depend on inputs that outlive the binary version - record them:
r1041_e82_400bps_sup_v500). There is NO auto-detection; --model_path is mandatory and a mismatch silently degrades calls.pileup.pt/full_alignment.pt. v1 TensorFlow models do NOT load in v2._with_mv signal-aware) lives in the rerio clair3_models/ repo; only a subset is bundled.If code throws an error, introspect the installed tool (run_clair3.sh --help) and adapt the example to the actual API rather than retrying.
"Call variants from my long reads" -> Run Clair3 with the model that matches how the reads were basecalled, phase, and benchmark with stratification - because the model string, not the command, determines accuracy.
run_clair3.sh --bam_fn=aln.bam --ref_fn=ref.fa --output=out/ --threads=16 --platform=ont --model_path=/models/r1041_e82_400bps_sup_v500Scope: germline diploid SNPs + small indels. NOT structural variants (-> structural-variants), NOT somatic/mosaic (-> ClairS/ClairS-TO), NOT RNA (-> Clair3-RNA).
Clair3's accuracy is gated by two facts a naive user misses:
--model_path at a specific model folder. Three axes must ALL match: chemistry (r941 vs r1041), basecaller tier (fast/hac/sup), and basecaller version (g5014/v430/v500/v520), plus the optional _with_mv signal-aware axis if the BAM has Dorado mv tags. Wrong model = no crash, no warning, measurably worse calls (indels most). Derive the model from the basecaller string in the run metadata; pick the model version closest to but not above the basecaller version.Clair3 "symphonizes" two networks: a fast pileup model (summarized per-position statistics) that calls the large majority of sites, and a slow full-alignment model (haplotype-resolved read tensor) that re-evaluates only the uncertain subset. Internally Clair3 phases the top het-SNP pileup calls with WhatsHap, haplotags the BAM, and feeds the haplotagged reads to the full-alignment model - which is why read-based phasing buys ~6% indel F1, not cosmetics. Output: merge_output.vcf.gz (final).
Model name anatomy (r1041_e82_400bps_sup_v500): pore (r1041=R10.4.1), flowcell (e82), speed (400bps), basecaller tier (sup/hac/fast), basecaller version (v500=Dorado 5.0.0, g5014=Guppy 5.0.14). The _with_mv suffix uses Dorado move-table tags for best accuracy when present.
| Data | --platform | Model |
|---|---|---|
| ONT R10.4.1 sup, Dorado v5.x, mv tags present | ont | r1041_e82_400bps_sup_v520_with_mv |
| ONT R10.4.1 sup, Dorado v5.0.0 | ont | r1041_e82_400bps_sup_v500 |
| ONT R10.4.1 hac | ont | r1041_e82_400bps_hac_v500/_v520 |
| ONT R9.4.1 (any tier) | ont | r941_prom_sup_g5014 |
| PacBio HiFi Revio | hifi | hifi_revio |
| PacBio HiFi Sequel II | hifi | hifi_sequel2 |
| Illumina (supported) | ilmn | ilmn |
| PacBio CLR | - | not supported -> PEPPER-Margin-DeepVariant |
| Scenario | Tool | Why |
|---|---|---|
| Germline SNV/indel, single sample | Clair3 | this skill |
| Somatic, paired tumor-normal | ClairS | VAF-aware; Clair3 germline priors cannot find low-VAF somatic |
| Somatic, tumor-only | ClairS-TO | tumor-only ensemble |
| De novo / Mendelian trio | Clair3-Nova / Clair3-Trio | family-aware |
| Long-read RNA variants | Clair3-RNA | RNA model |
| ONT R10.4.1, also considering DeepVariant | either | neck-and-neck on R10 sup; native-ONT DeepVariant (Kolesnikov 2024) superseded PEPPER-Margin |
| Non-human / draft / bacterial reference | Clair3 + --include_all_ctgs | default calls only chr1-22,X,Y -> empty output otherwise |
| Cohort joint genotyping | Clair3 gVCF -> GLnexus | bcftools merge on gVCFs is NOT joint genotyping |
# Germline ONT calling (model MUST match the basecaller)
run_clair3.sh \
--bam_fn=aln.bam --ref_fn=ref.fa --output=clair3_out/ \
--threads=16 --platform=ont \
--model_path=/opt/models/r1041_e82_400bps_sup_v500
# final VCF: clair3_out/merge_output.vcf.gz
# Phase the final output VCF (WhatsHap); --longphase_for_phasing swaps only the INTERNAL
# phaser to LongPhase (faster, SV-aware). For a LongPhase-phased final VCF use
# --use_longphase_for_final_output_phasing instead of --enable_phasing.
run_clair3.sh ... --enable_phasing --longphase_for_phasing
# Phased calls go to clair3_out/phased_merge_output.vcf.gz; merge_output.vcf.gz stays UNPHASED.
# Non-human / draft assembly reference - call ALL contigs
run_clair3.sh ... --include_all_ctgs
# Targeted / amplicon panel
run_clair3.sh ... --bed_fn=panel.bed --gvcf
# Benchmark against GIAB with stratification (the step that reveals ONT indel errors)
hap.py giab_truth.vcf.gz clair3_out/merge_output.vcf.gz \
-f giab_confident.bed -r ref.fa --engine=vcfeval \
--stratification giab_stratifications.tsv -o bench/hg002Trigger: --model_path pointing at a model that does not match the basecaller chemistry/tier/version. Mechanism: no auto-detection; the wrong network runs. Symptom: no error, lower F1 (indels most). Fix: derive the model from the basecaller string; verify the folder exists (rerio for the full set); for v2 ensure .pt models.
Trigger: bacterial genome or draft assembly without chr1-22,X,Y names. Mechanism: Clair3 calls only standard human contigs by default. Symptom: near-empty VCF. Fix: --include_all_ctgs.
Trigger: reporting only whole-genome F1. Mechanism: ONT indel errors concentrate in homopolymer/STR/low-complexity strata. Symptom: ~99.5% global indel F1 but much lower in LowComplexity. Fix: stratify with GIAB BEDs (Dwarshuis 2024); use CMRG for medically relevant genes.
Trigger: lowering --snp_min_af/--indel_min_af to catch low-VAF variants. Mechanism: germline model expects ~0.5/1.0 allele fractions, is not VAF-aware. Symptom: germline-model false positives at low AF, missed true somatic. Fix: ClairS (paired) / ClairS-TO (tumor-only).
Trigger: an old TensorFlow model dir with Clair3 v2. Mechanism: v2 needs PyTorch .pt models. Symptom: model load failure. Fix: use pileup.pt/full_alignment.pt models (Converted Rerio).
| Threshold | Source | Rationale |
|---|---|---|
| Recommended depth ~20-60x | Clair3 guidance | sensitivity (hets, indels) falls off below ~20x; --min_coverage default 2 is a floor, not a recommendation |
| Phasing buys ~6% indel F1 | Zheng 2022 | haplotagged reads disambiguate indel alleles in repeats |
| ONT R10.4.1 sup: SNP F1 ~99.99%, indel F1 ~99.5% | GIAB benchmarks | indel residual lives in homopolymer/STR strata |
--var_pct_full 0.3 (default) | Clair3 README | fraction of low-quality pileup calls re-run by full-alignment; raise for recall, slower |
| Stratify with GIAB / CMRG | Dwarshuis 2024 | global F1 hides the ONT indel problem |
| Error / symptom | Cause | Solution |
|---|---|---|
| Empty/near-empty VCF on non-human ref | default calls only chr1-22,X,Y | --include_all_ctgs |
| Model fails to load | v1 TF model with v2 Clair3 | use .pt (PyTorch) models |
--model_path .../models/ont not found | no generic ont/hifi model | point at a specific model subfolder |
| Worse-than-expected indels | wrong-version or wrong-tier model | match the basecaller model exactly |
| "joint genotyping" gave odd merges | bcftools merge on gVCFs is not joint calling | use GLnexus |
| Looking for somatic/low-VAF variants | germline caller | use ClairS / ClairS-TO |
--MD; use minimap2 >=2.28)© GPTomics, 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 2 other files in long-read-sequencing/clair3-variants of GPTomics/bioSkills.
Open the folder on GitHubat commit d91ed3d
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 GPTomics/bioSkills, which our catalogue first saw on October 7, 2026.
Bio Long Read Sequencing Clair3 Variants 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 |
|---|---|---|---|---|---|---|
| Bio Long Read Sequencing Clair3 Variants this skillGPTomics/bioSkills | 1.2k | 1 repos | ~2.9k | Automated safety check: Pass | MIT | |
| tangermeme Genomic Model Analysisjmschrei/tangermeme | 318 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Cellxgene Censusdavila7/claude-code-templates | 33k | 11 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Pixi Environment Builderxuzhougeng/wisp-science | 1k | — | ~3.7k | Automated safety check: Pass | AGPL-3.0 | |
| Bio Imaging Mass Cytometry Cell SegmentationFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | 1 repos | ~1.7k | Automated safety check: Pass | None | |
| Bio Variant Calling DeepvariantFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | 1 repos | ~2.3k | Automated safety check: Pass | None |
jmschrei/tangermeme
Routes agents to the right tangermeme reference for analyzing trained genomic deep learning models, from attributions and motif experiments to variant effects and design.
davila7/claude-code-templates
Query CZ CELLxGENE Census (61M+ cells). An agent skill from davila7/claude-code-templates.
xuzhougeng/wisp-science
A skill your agent uses when creating, migrating, or debugging pixi environments, especially for scientific Python, bioinformatics, single-cell analysis, CUDA/PyTorch, Jupyter/VS Code kernels…
FreedomIntelligence/OpenClaw-Medical-Skills
Cell segmentation from multiplexed tissue images. An agent skill from FreedomIntelligence/OpenClaw-Medical-Skills.
FreedomIntelligence/OpenClaw-Medical-Skills
Deep learning-based variant calling with Google DeepVariant.
BIMSBbioinfo/flexynesis
Run flexynesis, a deep-learning suite for multi-omics data integration and clinical outcome prediction (drug response, cancer subtyping, survival analysis).
GPTomics/bioSkills
Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO.
GPTomics/bioSkills
Installs the bioSkills collection of 425 bioinformatics skills in one step, or only chosen categories, so sequencing, RNA-seq, single-cell and variant tasks get specialized help.
GPTomics/bioSkills
Write biological sequences to files (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO.
GPTomics/bioSkills
Soft- or hard-clips PCR primer footprints from aligned amplicon BAMs so primer bases stop masquerading as confirmed reference sequence.
GPTomics/bioSkills
Filters BAM alignments by FLAG bits, mapping quality and regions with samtools view or pysam, with recipes for common keep and drop cases.
GPTomics/bioSkills
Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam.
Categories
Calls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and…. Bio Long Read Sequencing Clair3 Variants is an agent skill from GPTomics/bioSkills. Calls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and basecaller-version-matched model, enabling read-based phasing, and benchmarking against GIAB with stratification.
Bio Long Read Sequencing Clair3 Variants fits situations like: calling germline SNVs/indels from ONT; choosing a Clair3 model; phasing variants; benchmarking long-read calls.
Run `npx skills add GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a claude-code`. Or copy the skill folder (long-read-sequencing/clair3-variants in GPTomics/bioSkills) into .claude/skills/bio-long-read-sequencing-clair3-variants in your project. Claude Code loads it when a task matches its description.
Run `npx skills add GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a codex`. Or copy the skill folder (long-read-sequencing/clair3-variants in GPTomics/bioSkills) into .agents/skills/bio-long-read-sequencing-clair3-variants 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 GPTomics/bioSkills --skill bio-long-read-sequencing-clair3-variants -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bio-long-read-sequencing-clair3-variants, .gemini/skills/bio-long-read-sequencing-clair3-variants, .github/skills/bio-long-read-sequencing-clair3-variants and .opencode/skills/bio-long-read-sequencing-clair3-variants in your project.
Going by SKILL.md and its folder, Bio Long Read Sequencing Clair3 Variants needs a shell for the scripts in its folder. Our summary lists: A Bash shell.
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. Review the folder before installing.
Bio Long Read Sequencing Clair3 Variants is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k 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.
Skills that share tags, products or a category with Bio Long Read Sequencing Clair3 Variants: tangermeme Genomic Model Analysis (jmschrei/tangermeme, 318 stars), Cellxgene Census (davila7/claude-code-templates, 33k stars), Pixi Environment Builder (xuzhougeng/wisp-science, 1k stars) and Bio Imaging Mass Cytometry Cell Segmentation (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
GPTomics (a GitHub organization) maintains it in GPTomics/bioSkills, which has 1,218 GitHub stars. The repository holds 559 skills in this directory. The repository was last updated on August 15, 2026.
Source: GPTomics/bioSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.