AD
Data & Repro
Adaptyv
Adaptyv is a cloud laboratory platform that provides automated protein testing and validation services. Submit protein sequences via API or…
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Data & Repro
TO
tooluniverse-antibody-engineering
Maintainer FreedomIntelligence · Last updated April 1, 2026
Comprehensive antibody engineering and optimization for therapeutic development. Covers humanization, affinity maturation, developability assessment, and immunogenicity prediction. Use when asked to optimize antibodies, humanize sequences, or engineer therapeutic antibodies from lead to clinical candidate.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-antibody-engineering
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- AI-guided antibody optimization pipeline from preclinical lead to clinical candidate. Covers sequence humanization, structure modeling, affinity optimization, developability assessment, immunogenicity prediction, and manufacturing feasibility.
- KEY PRINCIPLES: 1. Report-first approach - Create optimization report before analysis 2. Evidence-graded humanization - Score based on germline alignment and framework retention 3. Developability-focused - Assess aggregation, stability, PTMs, immunogenicity 4. Structure-guided - Use AlphaFold/PDB structures for CDR analysis 5. Clinical precedent - Reference approved antibodies for validation 6. Quantitative scoring - Developability score (0-100) combining multiple factors 7. English-first queries - Always use English terms in tool calls, even if user writes in another language. Respond in user's language.
Source Doc
Excerpt From SKILL.md
When to Use
Apply when user asks:
- "Humanize this mouse antibody sequence"
- "Optimize antibody affinity for [target]"
- "Assess developability of this antibody"
- "Predict immunogenicity risk for [sequence]"
- "Engineer bispecific antibody against [targets]"
- "Reduce aggregation in antibody formulation"
- "Design pH-dependent binding antibody"
- "Analyze CDR sequences and suggest mutations"
1. Report-First Approach (MANDATORY)
-
Create the report file FIRST:
- File name:
antibody_optimization_report.md - Initialize with section headers
- Add placeholder:
[Analyzing...]
- File name:
-
Progressively update as analysis completes
-
Output separate files:
optimized_sequences.fasta- All optimized variantshumanization_comparison.csv- Before/after comparisondevelopability_assessment.csv- Detailed scores
2. Documentation Standards (MANDATORY)
Every optimization MUST include:
Use cases
- Use when asked to optimize antibodies, humanize sequences, or engineer therapeutic antibodies from lead to clinical candidate.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
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