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Computational Chemistry

Browse agent skills for molecular simulations, drug discovery, and chemical analysis

Categories, GitHub stars, and source recency help organize and order the catalog. These signals are not an endorsement, quality certification, safety review, or guarantee of fit. Open a skill detail and inspect its source before use.

≥48 results

healthcare-cdss-patterns
246.1k
affaan-maffaan-m/ECC
臨床意思決定支援システム（CDSS）パターン、医学的推論、およびエビデンスベースの実装。
healthcare-cdss-patterns
246.1k
affaan-maffaan-m/ECC
Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows. Use when building clinical decision support — drug interaction checks, dose validation, clinical scoring, or alert severity.
evaluating-llms-harness
240.0k
NousResearchNousResearch/hermes-agent
lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).
faiss
240.0k
NousResearchNousResearch/hermes-agent
Fast vector similarity search at billion scale.
dspy
240.0k
NousResearchNousResearch/hermes-agent
DSPy: declarative LM programs, auto-optimize prompts, RAG.
drug-discovery
240.0k
NousResearchNousResearch/hermes-agent
Drug discovery: ChEMBL search, drug-likeness, interactions.
pinecone-research
240.0k
NousResearchNousResearch/hermes-agent
Agent RAG and long-term memory with Pinecone.
fs-notebook-tabs
93.6k
nexu-ionexu-io/open-design
A computer-science capstone: an on-device ML keyboard that predicts next words privately — problem, method, evaluation, and defense answers. Built as a decision-grade coursework defense deck for professor, defense committee.
shader-dev
93.6k
nexu-ionexu-io/open-design
GLSL shader techniques for ray marching, fluid simulation, particle systems, and procedural generation. Useful for hero visuals and motion stills.
ruview-advanced-sensing
92.6k
ruvnetruvnet/RuView
Advanced RuView capabilities — RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift, pre-movement intention signals, adversarial signal detection, and multistatic mesh security hardening. Use for research-grade or multi-node deployments.
ruview-applications
92.6k
ruvnetruvnet/RuView
Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually *do* something with a working RuView setup.
ruview-mmwave
92.6k
ruvnetruvnet/RuView
Set up and run RuView mmWave / FMCW radar sensing — ESP32-C6 + Seeed MR60BHA2 (60 GHz, heart rate / breathing rate / presence) and HLK-LD2410 (24 GHz, presence + distance), plus mmWave↔WiFi-CSI sensor fusion (48-byte fused vitals, MR60BHA2/LD2410 auto-detect, v0.5.0+). Use when the deployment includes a millimetre-wave radar alongside or instead of WiFi CSI.
vector-search
70.2k
ruvnetruvnet/ruflo
Vector search via embeddings_* (large-scale HNSW) and ruvllm_hnsw_* (WASM router for ≤11 hot patterns), with RaBitQ 1-bit quantization for 32× memory reduction
cli-anything-unimol-tools
49.1k
HKUDSHKUDS/CLI-Anything
Interactive CLI for Uni-Mol molecular property prediction training and inference workflows.
cli-anything-unimol-tools
49.1k
HKUDSHKUDS/CLI-Anything
Interactive CLI for Uni-Mol molecular property prediction training and inference workflows.
use-vishot-with-capacitor
48.7k
moeru-aimoeru-ai/airi
Capture deterministic Capacitor application screens with Vishot. Use when the selected Vishot target is a Capacitor app and Codex must capture its locally served WebView at mobile dimensions or distinguish WebView evidence from native-shell evidence.
use-vishot-with-electron
48.7k
moeru-aimoeru-ai/airi
Capture deterministic Electron windows with Vishot. Use when the selected Vishot target is an Electron application and Codex must identify, prepare, and capture one or more renderer windows without relying on window creation order or agent-browser.
adaptyv
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
cirq
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
datamol
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
deepchem
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.
depmap
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets.
diffdock
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
DiffDock and DiffDock-L molecular docking. Use for protein-small-molecule pose prediction from PDB or sequence plus SMILES/SDF/MOL2, batch docking, virtual screening, and pose-confidence interpretation. Not for binding affinity prediction.
fluidsim
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Plan, configure, inspect, restart, and analyze bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.
histolab
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing, tissue detection, tile extraction, and stain normalization for H&E images. Best for simple pipelines, dataset preparation, and quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
imaging-data-commons
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Query and download public cancer imaging data from NCI Imaging Data Commons. Invoke for any question about IDC collections, cancer imaging datasets, DICOM data access, radiology (CT, MR, PET) or pathology AI training sets, metadata queries, visualization, or license checks — even when the user doesn't explicitly mention "IDC". No authentication required.
matchms
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Process, clean, compare, and search tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.
medchem
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.
molecular-dynamics
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, run energy minimization and production MD, analyze trajectories (RMSD, RMSF, contact maps, free energy surfaces). For structural biology, drug binding, and biophysics.
molfeat
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
openpiv
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Particle Image Velocimetry (PIV) analysis with OpenPIV. Use when extracting velocity fields from PIV image pairs, analyzing fluid dynamics or flow visualization experiments, cross-correlating interrogation windows, validating and replacing spurious PIV vectors, or computing vorticity, strain rate, and turbulence statistics from measured velocity fields.
pkpd-modeling
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".
pyopenms
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Complete mass spectrometry analysis platform. Use for proteomics and metabolomics workflows—feature detection, peptide/protein identification, label-free and isobaric quantification, adduct/accurate-mass annotation, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. For simple spectral comparison and small-molecule library matching use matchms.
qiskit
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Build, simulate, transpile, and execute quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.
qutip
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Simulate and audit closed and open quantum-system models with QuTiP 5, including deterministic, trajectory, steady-state, spectral, and phase-space workflows. Use for local quantum-dynamics work where physical assumptions, dimensions, and numerical convergence must be explicit.
rdkit
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
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.
rowan
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
stable-baselines3
43.3k
K-Dense-AIK-Dense-AI/scientific-agent-skills
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.
embedding-strategies
39.4k
wshobsonwshobson/agents
Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.
math-olympiad
35.8k
anthropicsanthropics/claude-plugins-official
Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.
digital-forensics
34.8k
zhaoxuya520zhaoxuya520/reverse-skill
Use for authorized digital forensics including memory dumps, disk timelines, PCAP investigation, artifact triage, and IR evidence preservation.

Skill content language: Chinese

llm-security
34.8k
zhaoxuya520zhaoxuya520/reverse-skill
Use for authorized security assessment of LLM applications and AI agents, including prompt injection, tool abuse, RAG exposure, memory poisoning, and model supply-chain risks.

Skill content language: Chinese

malware-analysis
34.8k
zhaoxuya520zhaoxuya520/reverse-skill
Use when analyzing suspected malware through static, dynamic, and behavioral techniques, including IOC extraction, YARA or Sigma rules, sandboxing, and anti-analysis behavior.

Skill content language: Chinese

ot-ics
34.8k
zhaoxuya520zhaoxuya520/reverse-skill
Use for authorized OT/ICS security assessment covering Purdue model zoning, PLC/SCADA exposure, industrial protocol discovery, and safe passive-first evaluation.

Skill content language: Chinese

radio-sdr
34.8k
zhaoxuya520zhaoxuya520/reverse-skill
Use for authorized RF/SDR security research including signal identification, replay feasibility study in shielded labs, and wireless protocol analysis outside classic Wi-Fi.

Skill content language: Mixed languages

analyzing-campaign-attribution-evidence
32.0k
mukul975mukul975/Anthropic-Cybersecurity-Skills
Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.
assessing-vector-and-embedding-weaknesses
32.0k
mukul975mukul975/Anthropic-Cybersecurity-Skills
Test RAG vector stores (Pinecone, Qdrant, Weaviate, Chroma, pgvector, FAISS) for embedding inversion, cross-tenant data leakage, and data poisoning per OWASP LLM08:2025. Use when performing an authorized security assessment of a RAG pipeline's retrieval layer or auditing multi-tenant vector-store isolation.
correlating-security-events-in-qradar
32.0k
mukul975mukul975/Anthropic-Cybersecurity-Skills
Correlates security events in IBM QRadar SIEM using AQL (Ariel Query Language), custom rules, building blocks, and offense management to detect multi-stage attacks across network, endpoint, and application log sources. Use when SOC analysts need to investigate QRadar offenses, build correlation rules, or tune detection logic for reducing false positives.