--- name: 'hemoglobinopathy-analysis-agent' description: 'AI-powered analysis of hemoglobin disorders including sickle cell disease, thalassemias, and variant hemoglobins using HPLC, electrophoresis, and molecular data.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- # Hemoglobinopathy Analysis Agent The **Hemoglobinopathy Analysis Agent** provides comprehensive AI-driven analysis of hemoglobin disorders. It integrates HPLC chromatograms, electrophoresis patterns, CBC parameters, and molecular genetics for diagnosis and management of sickle cell disease, thalassemias, and variant hemoglobins. ## When to Use This Skill * When interpreting HPLC hemoglobin chromatograms for variant identification. * To diagnose and classify thalassemia syndromes (α, β, δβ). * For comprehensive sickle cell disease phenotype assessment. * When correlating genotype with clinical phenotype severity. * To guide hydroxyurea dosing and transfusion management. ## Core Capabilities 1. **HPLC Interpretation**: AI pattern recognition for hemoglobin variant identification from HPLC chromatograms. 2. **Thalassemia Classification**: Distinguish α-thalassemia (silent carrier to Hb Bart's) and β-thalassemia (minor to major). 3. **Sickle Cell Phenotyping**: Integrate HbS%, HbF%, α-globin status for phenotype prediction. 4. **Variant Identification**: Database matching for >1,500 known hemoglobin variants. 5. **Molecular Correlation**: Link genetic variants (HBB, HBA1/2) to protein phenotypes. 6. **Management Guidance**: Treatment recommendations based on disease severity. ## Hemoglobin Pattern Analysis | Condition | HbA | HbA2 | HbF | Variants | RBC Indices | |-----------|-----|------|-----|----------|-------------| | Normal adult | 96-98% | 2-3% | <1% | - | Normal | | β-thal trait | 92-95% | 3.5-7% | 1-3% | - | Microcytic | | β-thal major | 0-10% | Variable | 90-95% | - | Severe anemia | | α-thal trait | 97-98% | 2-3% | <1% | - | Microcytic | | HbH disease | 70-90% | 1-2% | <1% | HbH 5-30% | Moderate anemia | | Sickle trait | 55-60% | 2-3% | <1% | HbS 38-45% | Normal | | Sickle cell | 0% | 2-3% | 2-20% | HbS 80-95% | Sickle cells | ## Workflow 1. **Input**: HPLC chromatogram, CBC with indices, peripheral smear findings, molecular data (if available). 2. **Pattern Recognition**: AI analysis of HPLC retention times and peak areas. 3. **Variant Matching**: Compare against hemoglobin variant database. 4. **RBC Correlation**: Integrate MCV, MCH, RDW, reticulocyte count. 5. **Phenotype Classification**: Assign clinical phenotype category. 6. **Management**: Generate treatment and monitoring recommendations. 7. **Output**: Diagnosis, variant identification, clinical classification, management plan. ## Example Usage **User**: "Interpret this HPLC chromatogram showing an abnormal peak and correlate with the CBC findings." **Agent Action**: ```bash python3 Skills/Hematology/Hemoglobinopathy_Analysis_Agent/hb_analyzer.py \ --hplc_data chromatogram.csv \ --retention_times peak_times.json \ --cbc cbc_results.json \ --peripheral_smear smear_findings.txt \ --molecular hbb_sequencing.vcf \ --output hb_report.json ``` ## Key Hemoglobin Variants | Variant | Mutation | HPLC Window | Clinical Significance | |---------|----------|-------------|----------------------| | HbS | β6 Glu→Val | S window | Sickling disorders | | HbC | β6 Glu→Lys | C window | HbC disease, HbSC | | HbE | β26 Glu→Lys | A2/E window | Common in SE Asia | | HbD-Punjab | β121 Glu→Gln | D window | HbSD-Punjab | | Hb Lepore | δβ fusion | S window | Thalassemia | | HbH | β4 tetramer | Fast band | α-thalassemia | | Hb Bart's | γ4 tetramer | Very fast | Hydrops fetalis | ## AI/ML Components **HPLC Pattern Recognition**: - CNN trained on 50,000+ chromatograms - Identifies peaks by retention time and shape - Quantifies hemoglobin fractions - Flags unusual patterns for review **Phenotype Prediction**: - Gradient boosting model - Features: Hb%, HbF%, α-globin genotype, F-cell distribution - Predicts clinical severity (mild/moderate/severe) - VOC risk, stroke risk, TCD velocity correlation **Genotype-Phenotype Correlation**: - Database of published correlations - Modifier genes (BCL11A, HBS1L-MYB, α-globin) - Pharmacogenomics (HU response prediction) ## Clinical Decision Support **Hydroxyurea Candidacy**: - Severe phenotype - ≥3 pain crises/year - ACS history - Stroke prevention **Transfusion Protocols**: - Simple vs exchange transfusion - Target HbS% thresholds - Iron chelation monitoring **Monitoring Schedule**: - LDH, reticulocytes, bilirubin - Ferritin for transfused patients - TCD for children with SCD ## Prerequisites * Python 3.10+ * PyTorch for image/signal analysis * Hemoglobin variant databases * Clinical lab interface ## Related Skills * Blood_Smear_Analysis - For morphology assessment * Variant_Interpretation - For molecular findings * Flow_Cytometry_AI - For F-cell quantification ## Newborn Screening Integration - Interpret newborn screening HPLC patterns - Distinguish FAS (sickle trait) from FS (sickle disease) - Flag FAE (HbE), FAC (HbC), F-only (β-thal major) - Generate confirmatory testing recommendations ## Author AI Group - Biomedical AI Platform --- Source attribution: FreedomIntelligence Original project: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 FridrichMethod Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. --- NOTE ON BUNDLED CONTENT This repository aggregates skills from multiple upstream projects (see the README for the source list). Each `skills//` directory may carry its own license inherited from its upstream source. The MIT license above applies to this repository's curation and the scripts/workflows in `/`, `/scripts/`, and `/.github/` — not to the upstream skill content itself. Consult the upstream repository linked in the README and any LICENSE file inside a skill directory before reusing skill content commercially. # Mega AI Hub resource metadata Creator / publisher: FreedomIntelligence Original project: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills Attribution basis: Exact package in biomedical source index and publisher source table Fields of work: Healthcare & Life Sciences Roles: Clinical Research, Health Informatics, Medical Writer Specialties: Specialty not specified Tools: Hplc, Electrophoresis Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: f18b2ab149beaf09430c372cc132c17d13d4796d5e4fb25a37f1de0234d68b67 Metadata reviewed: 2026-10-27 This metadata supersedes earlier Mega AI Hub catalog attribution. Original instruction and supporting files are preserved.