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OpenClaw-Medical-Skills crispr-offtarget-predictor

<!--

install
source · Clone the upstream repo
git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/crispr-offtarget-predictor" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-crispr-offtarget-predictor && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/crispr-offtarget-predictor" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-crispr-offtarget-predictor && rm -rf "$T"
manifest: skills/crispr-offtarget-predictor/SKILL.md
tags
#crispr-analysis#genomics#sequence-matching#pam-validation
source content
<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

name: 'crispr-offtarget-predictor' description: 'Predicts potential off-target sites for a given sgRNA sequence using mismatch analysis.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

CRISPR Off-Target Predictor

This skill identifies potential off-target binding sites for a specific sgRNA sequence. It helps researchers assess the specificity of their CRISPR design.

When to Use This Skill

  • Designing new CRISPR experiments.
  • Validating sgRNA specificity before synthesis.
  • Analyzing potential safety risks in gene editing protocols.

Core Capabilities

  1. Mismatch Scoring: Calculates mismatch penalties for potential sites.
  2. PAM Validation: Filters targets based on PAM (Protospacer Adjacent Motif) compatibility.
  3. Risk Assessment: Categorizes off-targets as Low, Medium, or High risk.

Workflow

  1. Input: sgRNA sequence (20nt) and PAM (e.g., NGG).
  2. Analysis: Scans a reference library (mocked for this version) for similar sequences.
  3. Output: List of potential off-targets with locations and risk scores.

Example Usage

User: "Check sgRNA 'GAGTCCGAGCAGAAGAAGAA' for off-targets."

Agent Action:

python3 Skills/Genomics/CRISPR_Prediction/impl.py --sequence GAGTCCGAGCAGAAGAAGAA --pam NGG
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->