Claude Skills by FreedomIntelligence

Automate payer review of prior authorization (PA) requests. This skill should be used when users say "Review this PA request", "Process prior authorization for [procedure]", "Assess medical necessity", "Generate PA decision", or when processing clinical documentation for coverage policy validation and authorization decisions.

Unified personal genomic profile report — reads a PatientProfile JSON and synthesizes all skill results into a single "Your Genomic Profile" document.

--> --- name: 'protac-design-agent' description: 'AI-powered PROTAC (Proteolysis Targeting Chimera) design for targeted protein degradation, integrating ternary complex prediction, linker optimization, and ADMET modeling.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **PROTAC Design Agent** provides AI-assisted design of Proteolysis Targeting Chimeras (PROTACs) for targeted protein degradati...

End-to-end guidance for protein design pipelines. Use this skill when: (1) Starting a new protein design project, (2) Need step-by-step workflow guidance, (3) Understanding the full design pipeline, (4) Planning compute resources and timelines, (5) Integrating multiple design tools. For tool selection, use binder-design. For QC thresholds, use protein-qc.

Quality control metrics and filtering thresholds for protein design. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage filtering pipelines, (5) Computing PyRosetta interface metrics (dG, SC, dSASA), (6) Checking biophysical properties (instability, GRAVY, pI), (7) Ranking designs with composite s...

--> --- name: 'protein-structure-prediction' description: 'Predicts 3D protein structures from amino acid sequences using ESMFold or AlphaFold3 (mock).' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Protein Structure Prediction Skill** provides an interface to state-of-the-art folding models. It takes an amino acid sequence and returns a PDB file or structure metrics (pLDDT).

Design protein sequences using ProteinMPNN inverse folding. Use this skill when: (1) Designing sequences for RFdiffusion backbones, (2) Redesigning existing protein sequences, (3) Fixing specific residues while designing others, (4) Optimizing sequences for expression or stability, (5) Multi-state or negative design. For backbone generation, use rfdiffusion or bindcraft. For ligand-aware design, use ligandmpnn. For solubility optimization, use solublempnn.

--> --- name: 'prs-net-deep-learning-agent' description: 'Geometric deep learning-based polygenic risk score prediction using PRS-Net for modeling gene interactions, enhanced disease prediction, and cross-ancestry portability.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **PRS-Net Deep Learning Agent** implements interpretable geometric deep learning for polygenic risk score prediction. PRS...

Analyzes events through psychological lens using cognitive psychology, social psychology, developmental psychology, clinical psychology, and neuroscience. Provides insights on behavior, cognition, emotion, motivation, group dynamics, decision-making biases, mental health, and individual differences. Use when: Behavioral patterns, decision-making, group behavior, mental health, leadership, persuasion, trauma, development. Evaluates: Cognitive processes, emotional responses, motivations, biases...

Search PubMed for scientific literature. Use when the user asks to find papers, search literature, look up research, find publications, or asks about recent studies. Triggers on "pubmed", "papers", "literature", "publications", "research on", "studies about".

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.

--> --- name: radgpt-radiology-reporter description: Radiology Reporter keywords: - radiology - report-generation - patient-friendly - summarization - explanation measurable_outcome: Generate a patient-friendly explanation of a radiology report with <1% hallucination rate within 30 seconds. license: MIT metadata: author: Stanford Medicine version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - read_file --- An LLM-based agent designed to summarize and explai...

--> --- name: 'radiomics-pathomics-fusion-agent' description: 'AI-powered multimodal fusion of radiology (CT/MRI/PET) and pathology (H&E/IHC) imaging with clinical and genomic data for comprehensive cancer diagnostics and treatment prediction.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Radiomics Pathomics Fusion Agent** integrates multimodal medical imaging data from radiology (CT, MRI,...

Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.

Trauma-informed AI moderator for addiction recovery communities. Applies harm reduction principles, honors 12-step traditions, distinguishes healthy conflict from abuse, detects crisis posts.

--> --- name: 'regulatory-drafter' description: 'Automates the drafting of regulatory documents (e.g., FDA CTD sections) with citation management and audit trails.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- This skill assists regulatory affairs professionals by automatically generating sections of the Common Technical Document (CTD) from raw data and literature. It focuses on accuracy, tracea...

--> --- name: 'regulatory-drafting' description: 'Regulatory Drafting agent for healthcare workflows.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- This skill implements the Regulatory Drafting workflow using Anthropic's Claude.

Export any bioinformatics analysis as a reproducible bundle with Conda environment, Singularity container definition, and Nextflow pipeline.

--> --- name: 'research-literature' description: 'Research Literature agent for healthcare workflows.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- This skill implements the Research Literature workflow using Anthropic's Claude.

Generate protein backbones using RFdiffusion, a diffusion-based generative model for de novo protein structure generation. Use this skill when: (1) Designing binder scaffolds for a target protein, (2) Generating novel protein backbones from scratch, (3) Scaffolding functional motifs into new proteins, (4) Specifying hotspot residues for interface design, (5) Creating symmetric oligomers. For sequence design after backbone generation, use proteinmpnn. For structure validation, use alphafold o...

--> --- name: 'rna-velocity-agent' description: 'AI-powered RNA velocity analysis for predicting cellular state transitions, differentiation trajectories, and dynamic gene regulation from single-cell RNA sequencing data.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **RNA Velocity Agent** analyzes RNA velocity from single-cell RNA sequencing to predict cellular state transitions, differentia...

--> --- name: 'scfoundation-model-agent' description: 'Unified agent for leveraging single-cell foundation models (scGPT, scBERT, Geneformer, scFoundation) for cross-species annotation, perturbation prediction, and gene network inference.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **scFoundation Model Agent** provides a unified interface to leverage state-of-the-art single-cell foundation...

Research ideation partner. Generate hypotheses, explore interdisciplinary connections, challenge assumptions, develop methodologies, identify research gaps, for creative scientific problem-solving.

Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.

--> --- name: scientific-manuscript description: "High-impact scientific manuscript preparation for journals like Nature, Blood, Cell. Use when writing abstracts, introductions, methods, results, discussions, or figure legends. Includes citation management, statistical reporting standards, ICMJE guidelines, and journal-specific formatting for hematology/oncology publications." license: Proprietary ---

Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process: (1) create section outlines with key points using research-lookup, (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.

Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad.

--> --- name: scrna-qc description: Execute the MAD-based single-cell RNA-seq QC workflow (scripts + Python API) to filter low-quality cells and emit reports plus filtered AnnData files. measurable_outcome: Produce filtered .h5ad files, before/after plots, and qc_summary.json within 20 minutes per dataset. allowed-tools: - read_file - run_shell_command ---

RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

--> --- name: search-strategy description: Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies. keywords: - search - query-decomposition - ranking - multi-source - strategy measurable_outcome: Successfully decomposes 100% of complex queries into source-specific sub-queries targeting relevant databa...

Sequence QC, alignment, and BAM processing. Wraps FastQC, BWA/Bowtie2, SAMtools for automated read-to-BAM pipelines.

--> --- name: 'simo-multiomics-integration-agent' description: 'AI-powered spatial integration of multi-omics datasets using probabilistic alignment for comprehensive tissue atlas construction and cellular state mapping.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **SIMO Multiomics Integration Agent** performs spatial integration of multi-omics datasets through probabilistic alignment. Unl...

Orchestrate multi-simulation campaigns including parameter sweeps, batch jobs, and result aggregation. Use for running parameter studies, managing simulation batches, tracking job status, combining results from multiple runs, or automating simulation workflows.

Validate simulations before, during, and after execution. Use for pre-flight checks, runtime monitoring, post-run validation, diagnosing failed simulations, checking convergence, detecting NaN/Inf, or verifying mass/energy conservation.

Guide Claude through SCSA, MetaTiME, CellVote, CellMatch, GPTAnno, and weighted KNN transfer workflows for annotating single-cell modalities.

Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.

Run omicverse's CellPhoneDB v5 wrapper on annotated single-cell data to infer ligand-receptor networks and produce CellChat-style visualisations.

Guide Claude through omicverse's single-cell clustering workflow, covering preprocessing, QC, multimethod clustering, topic modeling, cNMF, and cross-batch integration as demonstrated in t_cluster.ipynb and t_single_batch.ipynb.

Checklist-style reference for OmicVerse downstream tutorials covering AUCell scoring, metacell DEG, and related exports.

Quick-reference sheet for OmicVerse tutorials spanning MOFA, GLUE pairing, SIMBA integration, TOSICA transfer, and StaVIA cartography.

Walk through omicverse's single-cell preprocessing tutorials to QC PBMC3k data, normalise counts, detect HVGs, and run PCA/embedding pipelines on CPU, CPU–GPU mixed, or GPU stacks.

Map scRNA-seq atlases onto spatial transcriptomics slides using omicverse's Single2Spatial workflow for deep-forest training, spot-level assessment, and marker visualisation.

Generate SLURM `sbatch` job scripts and sanity-check HPC resource requests (nodes, tasks, CPUs, memory, GPUs) for simulation runs. Use when preparing submission scripts, deciding MPI vs MPI+OpenMP layouts, standardizing `#SBATCH` directives, or debugging job launch configuration (`sbatch`/`srun`).

Solubility-optimized protein sequence design using SolubleMPNN. Use this skill when: (1) Designing for E. coli expression, (2) Optimizing solubility of designed proteins, (3) Reducing aggregation propensity, (4) Need high-yield expression, (5) Avoiding inclusion body formation. For standard design, use proteinmpnn. For ligand-aware design, use ligandmpnn.