Agent skill

bio-genome-engineering-off-target-prediction

Predict CRISPR off-target sites using Cas-OFFinder and CFD scoring algorithms. Identify potential unintended cleavage sites genome-wide and assess guide specificity. Use when evaluating guide RNA specificity or selecting guides with minimal off-target risk.

FreedomIntelligencegithub.com/FreedomIntelligenceGitHub ↗
claude-codeships scripts
Install
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-genome-engineering-off-target-prediction --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 8 KB
Bundled scripts: yes
Path: skills/bio-genome-engineering-off-target-prediction/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,909
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: pandas 2.2+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Off-Target Prediction **"Check my guide RNA for off-target sites"** → Search the genome for potential unintended cleavage sites allowing mismatches, then score each off-target by cutting frequency determination (CFD) to assess guide specificity. - CLI: `cas-offinder` for genome-wide off-target search - Python: CFD scoring with mismatch penalty matrices ## Cas-OFFinder (CLI) Cas-OFFinder searches genomes for potential off-target sites allowing mismatches. ```bash # Input file format (input.txt): # Line 1: Path to genome directory (2bit or fasta index) # Line 2: PAM pattern (N = any, R = A/G, Y = C/T) # Line 3+: Guide sequences with mismatch tolerance # Example input.txt: # /path/to/genome # NNNNNNNNNNNNNNNNNNNNNGG # ATCGATCGATCGATCGATCG

What's inside
Steps it walks through
  1. Version Compatibility
  2. Cas-OFFinder (CLI)
  3. Cas-OFFinder Input Preparation
  4. Parse Cas-OFFinder Output
  5. CFD Score Calculation
  6. Aggregate Off-Target Score
  7. CRISPOR-style Analysis
  8. Related Skills
Ships with 2 files
  • examples/off_target_analysis.py
  • usage-guide.md
Commands it runs
Input file format (input.txt):
Line 1: Path to genome directory (2bit or fasta index)
Line 2: PAM pattern (N = any, R = A/G, Y = C/T)
Line 3+: Guide sequences with mismatch tolerance
Example input.txt:
NNNNNNNNNNNNNNNNNNNNNGG
ATCGATCGATCGATCGATCGNNN 4
Run Cas-OFFinder
cas-offinder input.txt C output.txt  # C = use CPU
cas-offinder input.txt G output.txt  # G = use GPU (faster)
More from OpenClaw-Medical-Skills
All skills →
About this skill
What does the bio-genome-engineering-off-target-prediction skill do?

Predict CRISPR off-target sites using Cas-OFFinder and CFD scoring algorithms. Identify potential unintended cleavage sites genome-wide and assess guide specificity. Use when evaluating guide RNA specificity or selecting guides with minimal off-target risk.

How do I install it?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-genome-engineering-off-target-prediction --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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