Alphagenome Single Variant Analysis
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.
Designs donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the…
$ npx skills add GPTomics/bioSkills --skill bio-genome-engineering-hdr-template-design -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install GPTomics/bioSkills bio-genome-engineering-hdr-template-design --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/genome-engineering/hdr-template-design .claude/skills/bio-genome-engineering-hdr-template-design && 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-genome-engineering-hdr-template-design" agent skill from https://github.com/GPTomics/bioSkills/tree/main/genome-engineering/hdr-template-design into .claude/skills/bio-genome-engineering-hdr-template-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-genome-engineering-hdr-template-design", 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/genome-engineering/hdr-template-designType 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-genome-engineering-hdr-template-design -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install GPTomics/bioSkills bio-genome-engineering-hdr-template-design --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/genome-engineering/hdr-template-design .agents/skills/bio-genome-engineering-hdr-template-design && 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-genome-engineering-hdr-template-design" agent skill from https://github.com/GPTomics/bioSkills/tree/main/genome-engineering/hdr-template-design into .agents/skills/bio-genome-engineering-hdr-template-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-genome-engineering-hdr-template-design", 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-genome-engineering-hdr-template-design -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install GPTomics/bioSkills bio-genome-engineering-hdr-template-design --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/genome-engineering/hdr-template-design .cursor/skills/bio-genome-engineering-hdr-template-design && 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-genome-engineering-hdr-template-design" agent skill from https://github.com/GPTomics/bioSkills/tree/main/genome-engineering/hdr-template-design into .cursor/skills/bio-genome-engineering-hdr-template-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-genome-engineering-hdr-template-design", 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 genome-engineering/hdr-template-design--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-genome-engineering-hdr-template-design -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install GPTomics/bioSkills bio-genome-engineering-hdr-template-design --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/genome-engineering/hdr-template-design .gemini/skills/bio-genome-engineering-hdr-template-design && 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-genome-engineering-hdr-template-design" agent skill from https://github.com/GPTomics/bioSkills/tree/main/genome-engineering/hdr-template-design into .gemini/skills/bio-genome-engineering-hdr-template-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-genome-engineering-hdr-template-design", 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-genome-engineering-hdr-template-designInstalls 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-genome-engineering-hdr-template-design -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/genome-engineering/hdr-template-design .github/skills/bio-genome-engineering-hdr-template-design && 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-genome-engineering-hdr-template-design" agent skill from https://github.com/GPTomics/bioSkills/tree/main/genome-engineering/hdr-template-design into .github/skills/bio-genome-engineering-hdr-template-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-genome-engineering-hdr-template-design", 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-genome-engineering-hdr-template-design -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-genome-engineering-hdr-template-design --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/genome-engineering/hdr-template-design .opencode/skills/bio-genome-engineering-hdr-template-design && 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-genome-engineering-hdr-template-design" agent skill from https://github.com/GPTomics/bioSkills/tree/main/genome-engineering/hdr-template-design into .opencode/skills/bio-genome-engineering-hdr-template-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-genome-engineering-hdr-template-design", 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-genome-engineering-hdr-template-designDesigns donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the…
Bio Genome Engineering Hdr Template Design is an agent skill from GPTomics/bioSkills. Designs donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the edit, and adding a mandatory codon-checked blocking (PAM/seed) mutation so the edited allele is not re-cut. Frames the HDR-vs-NHEJ-vs-MMEJ pathway competition, the MMEJ (PITCh) and homology-independent (HITI/HMEJ) alternatives for post-mitotic cells, ssODN strand/asymmetry choice, phosphorothioate end-protection, and…
Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `examples/hdr_template_design.py` and `usage-guide.md`).
It sits in Research & Science, covering Bioinformatics. The repository describes itself as: a set of SKILLS.md for doing bioinformatics with agents like claude code. The licence is MIT.
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 (Python), which the agent can run.
Shell commands in SKILL.md call:
pipFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
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 Genome Engineering Hdr Template Design loads about 4k tokens when it runs. Until then it costs about 194 tokens; SKILL.md has 1,956 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). 1,956 words, ~3,997 tokens.
.claude/skills/bio-genome-engineering-hdr-template-design/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: BioPython 1.83+, primer3-py 2.0+.
Before using code patterns, verify installed versions match. If versions differ:
pip show <package> then help(module.function) to check signaturesIf code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
primer3-py designs PRIMERS (use primer3.bindings.design_primers(seq_args, global_args); the camelCase designPrimers is deprecated since 1.0.0), not homology arms -- arm extraction and codon-aware blocking are the skill's own BioPython code. Design arms and guide against the actual cell line's sequence, not GRCh38 -- a SNP in an arm reduces annealing and a SNP in the PAM/seed can mean the guide does not cut.
"Design a donor for my CRISPR knock-in" -> Decide the format by edit size and whether the cell cycles, size the arms, confirm a guide cuts within ~10 bp of the edit, and add a codon-checked blocking mutation so the corrected allele cannot be re-cut.
Bio.Seq; primer3.bindings.design_primers() for arm-amplification and junction-validation primersA Cas9 double-strand break is repaired by whichever pathway wins a kinetic race, and in most cells the winner is classical NHEJ (fast, all cell-cycle phases). MMEJ (microhomology, S/G2) and HDR (template-dependent, S/G2 only) are minority players, so unenhanced HDR knock-in is typically single-digit to low-double-digit percent -- that is normal, not a failure. The donor is not "the sequence to insert"; it is the toolkit for tilting a race NHEJ is structurally favored to win. The corollary, and the field's most expensive misread: a donor with perfect arms but no blocking mutation gets its successful edit erased -- the corrected allele still has an intact protospacer + PAM, so Cas9 re-cuts it and NHEJ scars it, and the indel reads out as "HDR failed" (indistinguishable from low HDR). So when someone reports "low HDR, lots of indels," the first question is not "how long are the arms?" -- it is "does the donor disrupt the PAM or seed?" A blocking mutation is mandatory and must be codon-checked; without it the readout is re-cutting, not HDR.
| Pathway | Cell cycle | Template | Signature | Relevance |
|---|---|---|---|---|
| c-NHEJ | all phases (dominant) | none | indels | the competitor; the engine HITI exploits |
| MMEJ / alt-EJ (Pol theta) | S/G2 | 5-25 bp microhomology | microhomology-flanked deletions | the PITCh route |
| HDR / HR | S/G2 only | sister chromatid or exogenous donor | precise, scarless | the classic knock-in route; minority |
| SSA | S/G2 | repeats | deletion between repeats | nuisance |
End resection (cell-cycle-gated, licensed in S/G2; 53BP1-RIF1 protects ends/pro-NHEJ, BRCA1 antagonizes it/pro-HDR) decides the fork. Consequences: post-mitotic cells barely do HDR -> for neurons/muscle/in-vivo tissue, HITI/HMEJ (NHEJ-based) is the correct first choice, not a fallback. Timing RNP+donor delivery into S/G2 raises HDR (Lin 2014, up to ~38% in HEK293T) -- the donor is necessary but the cell-cycle state gates it.
| Format | Insert | Arms | Best for | Caveat |
|---|---|---|---|---|
| ssODN | <= ~50 bp edits | ~30-60 nt each (total ~120-200 nt) | point mutations, small tags, loxP | synthesis ceiling ~200 nt; strand choice contested |
| long ssDNA (Easi-CRISPR) | ~0.2-2 kb | ~50-100 nt | cassettes, floxed/conditional alleles, zygote KI | less toxic & less random integration than dsDNA; harder to make |
| dsDNA (PCR/linear) | ~0.1-1.5 kb | ~200-800 bp | medium cassettes | dsDNA is toxic (innate sensing) + random integration |
| plasmid / HMEJ | up to several kb | ~500-2000 bp | large insertions, conditional alleles | backbone integration risk; slowest |
| AAV6 | <= ~4.5 kb (ITR-to-ITR, arms included) | ~400 bp-1 kb | hard-to-transfect primary cells (HSPC, T, iPSC), in vivo | manufacturing cost; cargo cap is a hard wall |
Heuristics: point/small edit -> ssODN; 0.2-2 kb -> lssDNA over dsDNA (cleaner) for animal/zygote work; large cassette -> plasmid/HMEJ (lines) or AAV6+RNP (primary cells); post-mitotic -> HITI.
Richardson 2016 proposed an ssODN complementary to the non-target strand, asymmetric with the longer arm PAM-proximal (~91 nt) and the shorter PAM-distal (~36 nt). Subsequent systematic work could not reproduce this as universal: the optimal strand flips by locus and the asymmetric advantage often vanishes once both arms are >=30 nt. Treat it as a prior to test, not a law -- generate both strands and symmetric+asymmetric variants and test them. By contrast, phosphorothioate (PS) end-protection (2-3 terminal bases each end) is a near-universal cheap win (exonuclease resistance) -- encode these at opposite confidence levels.
| Situation | Route |
|---|---|
| Point/small edit, cycling cells | ssODN + HDR (with blocking mutation) |
| Medium/large cassette, cycling line | HDR (lssDNA/plasmid) or HMEJ |
| Large cassette, primary cells (HSPC/T/iPSC) | AAV6 donor + RNP + HDR |
| Clean zygote/animal KI, <=2 kb | lssDNA Easi-CRISPR + HDR |
| Trivial donor construction wanted | PITCh (MMEJ) |
| Non-dividing / post-mitotic / in vivo | HITI (or HMEJ) |
| Edit far from any cut / single base | -> base-editing-design or prime-editing-design (donor-free) |
Most enhancers are marginal, cell-type-specific, and frequently non-reproducible; the published fold-changes are line-specific maxima. A blocking mutation and a cut near the edit matter more than any small molecule.
Goal: Assemble a donor that incorporates the edit AND survives re-cutting, with primers to amplify the arms and genotype the junction.
Approach: Extract arms flanking the cut, insert the edit, then add a blocking mutation -- disrupt the PAM synonymously if a wobble option exists, else introduce silent seed mutations -- verifying the change does not alter the encoded amino acid. Use primer3-py for arm-amplification/junction primers. (See examples/hdr_template_design.py for codon-aware blocking and a primer3 call.)
from Bio.Seq import Seq
def synonymous_pam_block(codon_table, pam_codon, alt_codon):
'''Return True only if a PAM-disrupting codon swap keeps the same amino acid (silent).'''
return codon_table.get(pam_codon) == codon_table.get(alt_codon) # never mutate the PAM without this checkTrigger: low edit, mostly indels, no blocking mutation. Mechanism: the corrected allele keeps an intact PAM -> Cas9 re-cuts -> NHEJ scar. Symptom: indels indistinguishable from no-HDR. Fix: add a codon-checked PAM/seed blocking mutation; the readout was re-cutting, not HDR.
Trigger: best-cutting guide is 25 bp from the edit. Mechanism: HDR incorporation falls with distance. Symptom: only the blocking mutation is incorporated (useless silent-only allele) or no edit. Fix: choose a guide cutting within ~10 bp; if none, switch to base/prime editing.
Trigger: blindly changing the NGG's second G to A. Mechanism: the PAM may be in a coding frame. Symptom: an unintended missense/nonsense change. Fix: verify the swap is synonymous; else use silent seed mutations.
Trigger: a plasmid/PCR donor in iPSC/primary/zygotes. Mechanism: dsDNA toxicity + random integration. Symptom: low viability, random integrants. Fix: use lssDNA (Easi-CRISPR) or AAV6.
Trigger: ssODN/plasmid for neurons/in-vivo tissue. Mechanism: HDR runs only in S/G2. Symptom: essentially no knock-in. Fix: use HITI (NHEJ-based) or HMEJ.
Trigger: GRCh38 arms for a passaged/cancer line. Mechanism: line-specific SNPs in the arm or PAM/seed. Symptom: poor annealing or no cut. Fix: design against the cell line's actual sequence; account for ploidy/zygosity.
| Parameter | Value | Source |
|---|---|---|
| ssODN total length | ~120-200 nt | synthesis ceiling |
| ssODN arm | ~30-60 nt each | below ~30 HDR drops; above ~60 diminishing returns |
| dsDNA/plasmid arm | ~200-800 bp (up to ~2 kb) | ~500-800 bp common sweet spot |
| lssDNA insert | ~0.2-2 kb | Easi-CRISPR range |
| AAV cargo | <= ~4.5 kb (arms included) | packaging limit (hard wall) |
| PITCh microhomology | ~5-25 bp | MMEJ working range |
| Edit-to-cut distance | <= ~10 bp | HDR incorporation falls with distance (Paquet 2016) |
| Phosphorothioate | 2-3 terminal bases each end | exonuclease resistance |
| Cold shock | 32 C, 24-48 h | G2/M accumulation (Guo 2018) |
| Typical raw HDR | single-digit to ~20% (up to ~38-60% optimized) | minority pathway |
| Error / symptom | Cause | Solution |
|---|---|---|
| Low HDR, mostly indels | no blocking mutation (re-cutting) | add codon-checked PAM/seed block |
| Only the silent mutation incorporated | edit too far from cut | cut within ~10 bp or switch to base/prime editing |
| Toxicity / random integration | dsDNA in sensitive cells | lssDNA or AAV6 |
| No knock-in in neurons/in vivo | HDR donor in post-mitotic cells | HITI/HMEJ |
| AAV donor will not package | arms + insert exceed ~4.5 kb | shorten arms/insert; budget against the cap |
© 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 genome-engineering/hdr-template-design 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 Genome Engineering Hdr Template Design 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 Genome Engineering Hdr Template Design this skillGPTomics/bioSkills | 1.2k | 1 repos | ~4k | Automated safety check: Pass | MIT | |
| 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 | |
| Dbsnp Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.4k | Automated safety check: Notes | Apache-2.0 |
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.
aiming-lab/AutoResearchClaw
Runs a metabolic flux analysis from model loading to phenotype prediction and figures by handing work to four sub-agents in sequence.
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
Designs donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the…. Bio Genome Engineering Hdr Template Design is an agent skill from GPTomics/bioSkills. Designs donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the edit, and adding a mandatory codon-checked blocking (PAM/seed) mutation so the edited allele is not re-cut.
Bio Genome Engineering Hdr Template Design fits situations like: designing a donor for a point mutation; epitope/fluorophore tag; allele replacement; HDR efficiency is low.
Run `npx skills add GPTomics/bioSkills --skill bio-genome-engineering-hdr-template-design -a claude-code`. Or copy the skill folder (genome-engineering/hdr-template-design in GPTomics/bioSkills) into .claude/skills/bio-genome-engineering-hdr-template-design in your project. Claude Code loads it when a task matches its description.
Run `npx skills add GPTomics/bioSkills --skill bio-genome-engineering-hdr-template-design -a codex`. Or copy the skill folder (genome-engineering/hdr-template-design in GPTomics/bioSkills) into .agents/skills/bio-genome-engineering-hdr-template-design 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-genome-engineering-hdr-template-design -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-genome-engineering-hdr-template-design, .gemini/skills/bio-genome-engineering-hdr-template-design, .github/skills/bio-genome-engineering-hdr-template-design and .opencode/skills/bio-genome-engineering-hdr-template-design in your project.
Going by SKILL.md and its folder, Bio Genome Engineering Hdr Template Design needs Python for the scripts in its folder and the command-line tools its instructions call (pip). Our summary lists: Python 3.
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. 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 Genome Engineering Hdr Template Design is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4k tokens (SKILL.md is roughly 16k 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 Genome Engineering Hdr Template Design: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k 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.