> ## Documentation Index > Fetch the complete documentation index at: https://docs.kalarislabs.com/llms.txt > Use this file to discover all available pages before exploring further. # Skill catalog > All 281 research agent skills by category. # Skill catalog ## research-writing Scientific and research paper writing, grants, peer review, critical appraisal. * [`abstract-and-title`](/research-agent-skills/skills/abstract-and-title) — Write and sharpen research paper titles, abstracts (structured and unstructured), keywords, highlights, significance statements, graphical-abstract text and la… * [`cover-letter-to-editor`](/research-agent-skills/skills/cover-letter-to-editor) — Write journal submission cover letters, presubmission inquiries, transfer requests, and reviewer suggestion or exclusion lists that help a manuscript get past… * [`dhdna-profiler`](/research-agent-skills/skills/dhdna-profiler) — Extract cognitive patterns and thinking fingerprints from any text. * [`markdown-mermaid-writing`](/research-agent-skills/skills/markdown-mermaid-writing) — Writes scientific documents and documentation as markdown with embedded Mermaid diagrams as the canonical, git-diffable source format. * [`market-research-reports`](/research-agent-skills/skills/market-research-reports) — Build evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. * [`ml-paper-writing`](/research-agent-skills/skills/ml-paper-writing) — Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. * [`peer-review`](/research-agent-skills/skills/peer-review) — Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments. * [`rebuttal-and-response-to-reviewers`](/research-agent-skills/skills/rebuttal-and-response-to-reviewers) — Plan and write responses to peer review, including journal "response to reviewers" letters for revise-and-resubmit, conference rebuttals under strict length li… * [`reproducibility-statement`](/research-agent-skills/skills/reproducibility-statement) — Prepare the reproducibility, transparency and open-science parts of a paper, including data and code availability statements, reproducibility checklists (NeurI… * [`research-grants`](/research-agent-skills/skills/research-grants) — Guides writing of competitive research grant proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. * [`scholar-evaluation`](/research-agent-skills/skills/scholar-evaluation) — Provide qualitative-first, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with optional local qual… * [`scientific-critical-thinking`](/research-agent-skills/skills/scientific-critical-thinking) — Evaluate scientific claims and evidence quality. * [`scientific-writing`](/research-agent-skills/skills/scientific-writing) — Draft, revise, and audit scientific manuscripts or reports with explicit evidence provenance, reporting-guideline coverage, authorship accountability, confiden… * [`systems-paper-writing`](/research-agent-skills/skills/systems-paper-writing) — Provides paragraph-level structural blueprints for 10-12 page systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. * [`unslop-academic-writing`](/research-agent-skills/skills/unslop-academic-writing) — Remove AI slop from research writing so papers, theses, grant proposals, reviews and rebuttals read as written by a careful human expert. ## journal-formats Journal, conference and venue formatting: LaTeX templates, submission checklists. * [`acm-sigconf`](/research-agent-skills/skills/acm-sigconf) — Format ACM conference papers and journal articles with the acmart LaTeX class (sigconf, sigplan, acmsmall, acmlarge, acmtog, manuscript/review/anonymous modes)… * [`apa7`](/research-agent-skills/skills/apa7) — Format papers, theses and references in APA Style 7th edition for psychology, education, social sciences, nursing and business, covering student vs professiona… * [`arxiv-submission`](/research-agent-skills/skills/arxiv-submission) — Prepare and post preprints to arXiv without processing failures or leaks, covering TeX source packaging (.bbl, figures, case-sensitive paths), stripping privat… * [`cell-press`](/research-agent-skills/skills/cell-press) — Prepare manuscripts for Cell Press journals (Cell, Molecular Cell, Neuron, Immunity, Cell Reports, Cell Systems, iScience, Cell Metabolism, Current Biology and… * [`elsevier-cas`](/research-agent-skills/skills/elsevier-cas) — Prepare submissions to Elsevier journals (including The Lancet family style notes, Cell-independent Elsevier titles, and thousands of society journals) using t… * [`ieee-transactions`](/research-agent-skills/skills/ieee-transactions) — Format and submit papers to IEEE journals (Transactions, Journals, Letters, IEEE Access) and IEEE conferences using the IEEEtran LaTeX class or Word templates,… * [`nature-portfolio`](/research-agent-skills/skills/nature-portfolio) — Prepare manuscripts for Nature and Nature Portfolio journals (Nature, Nature Communications, Nature Methods, Nature Biotechnology, Scientific Reports and other… * [`plos`](/research-agent-skills/skills/plos) — Prepare manuscripts for PLOS journals (PLOS ONE, PLOS Biology, PLOS Computational Biology, PLOS Genetics, PLOS Medicine, PLOS Pathogens, PLOS Neglected Tropica… * [`science-aaas`](/research-agent-skills/skills/science-aaas) — Prepare manuscripts for Science and the Science family of journals (Science, Science Advances, Science Translational Medicine, Science Robotics, Science Immuno… * [`springer-lncs`](/research-agent-skills/skills/springer-lncs) — Format papers for Springer Lecture Notes in Computer Science (LNCS) and related proceedings series (LNAI, LNBI, CCIS) and Springer Nature journals using the ll… * [`venue-templates`](/research-agent-skills/skills/venue-templates) — Prepare journal manuscripts, conference papers, research posters, and grant documents using venue-specific formatting guidance and bundled LaTeX scaffolds. ## literature-review Literature search, systematic reviews, citation management and reference managers. * [`bgpt-paper-search`](/research-agent-skills/skills/bgpt-paper-search) — Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. * [`bibtex-hygiene`](/research-agent-skills/skills/bibtex-hygiene) — Clean, deduplicate and validate BibTeX/BibLaTeX bibliographies before submission. * [`citation-management`](/research-agent-skills/skills/citation-management) — Searches OpenAlex, PubMed, and Google Scholar, extracts metadata from DOIs, PMIDs, PMCIDs, arXiv IDs, and URLs via CrossRef, PubMed, and arXiv, then formats, d… * [`citation-verification`](/research-agent-skills/skills/citation-verification) — Verify that every reference in a manuscript really exists and matches its metadata, catching hallucinated, corrupted or mismatched citations before submission. * [`exa-search`](/research-agent-skills/skills/exa-search) — Web toolkit powered by Exa, tuned for scientific and technical content. * [`firecrawl-research-index`](/research-agent-skills/skills/firecrawl-research-index) — Query Firecrawl Research Index paper endpoints for topic discovery, source metadata, question-matched passages, and citation-neighbor expansion. * [`liteparse`](/research-agent-skills/skills/liteparse) — Local document and PDF parsing that returns spatial text with bounding boxes. * [`literature-review`](/research-agent-skills/skills/literature-review) — Runs systematic literature reviews by searching PubMed, arXiv, bioRxiv, and Semantic Scholar (plus web search via parallel-cli), screening studies, extracting… * [`markitdown`](/research-agent-skills/skills/markitdown) — Converts documents to Markdown with Microsoft MarkItDown (Python API, markitdown CLI, markitdown-ocr plugin, markitdown-mcp server), covering PDF, Word, PowerP… * [`open-notebook`](/research-agent-skills/skills/open-notebook) — Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. * [`paper-lookup`](/research-agent-skills/skills/paper-lookup) — Search 18 scholarly APIs for papers, preprints, citations, open-access full text, repository records, and journal OA status, and return results with reproducib… * [`paperclip`](/research-agent-skills/skills/paperclip) — Search and read full-text biomedical papers, FDA/PMDA/EMA regulatory documents, clinical trial registries, and UniProt/PDB/ChEMBL entries with the Paperclip CL… * [`paperzilla`](/research-agent-skills/skills/paperzilla) — Chat with your agent about projects, recommendations, and canonical papers in Paperzilla. * [`parallel-web`](/research-agent-skills/skills/parallel-web) — Runs the parallel-cli tool for web workflows: web search, URL and PDF extraction, deep research reports, structured data enrichment of supplied rows, FindAll e… * [`pyzotero`](/research-agent-skills/skills/pyzotero) — Reads and writes Zotero libraries from Python with pyzotero 1.13.0 and the Zotero Web API v3: items, collections, tags, attachments, saved searches, full-text… * [`reference-manager-interop`](/research-agent-skills/skills/reference-manager-interop) — Move and sync reference libraries between Zotero, Mendeley, EndNote, JabRef, Paperpile and writing tools (LaTeX/BibTeX, Word, Google Docs, Pandoc, Quarto, Over… * [`research-lookup`](/research-agent-skills/skills/research-lookup) — Compile current scholarly evidence for a scientific manuscript or research brief. * [`systematic-review-prisma`](/research-agent-skills/skills/systematic-review-prisma) — Plan, run and report systematic reviews and meta-analyses to PRISMA 2020 standards. ## ideation-and-design Hypothesis generation, experimental design, statistics planning, validation. * [`analytical-method-validation`](/research-agent-skills/skills/analytical-method-validation) — Plans and evaluates analytical method validation, verification, and transfer using Python scripts (plan\_validation, check\_response, check\_accuracy\_precision, c… * [`brainstorming-research-ideas`](/research-agent-skills/skills/brainstorming-research-ideas) — Guides researchers through structured ideation frameworks to discover high-impact research directions. * [`consciousness-council`](/research-agent-skills/skills/consciousness-council) — Run a multi-perspective Mind Council deliberation on any question, decision, or creative challenge. * [`creative-thinking-for-research`](/research-agent-skills/skills/creative-thinking-for-research) — Applies cognitive science frameworks for creative thinking to CS and AI research ideation. * [`experimental-design`](/research-agent-skills/skills/experimental-design) — Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interp… * [`hypogenic`](/research-agent-skills/skills/hypogenic) — Plans and audits use of ChicagoHAI HypoGeniC/HypoRefine for LLM-assisted hypothesis generation from labeled text datasets. * [`hypothesis-generation`](/research-agent-skills/skills/hypothesis-generation) — Formulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurem… * [`iso-standards-readiness`](/research-agent-skills/skills/iso-standards-readiness) — Prepares and structurally reviews readiness evidence for ISO management-system and laboratory-competence standards - ISO 13485 medical device QMS, ISO 14971 de… * [`relsa-severity-assessment`](/research-agent-skills/skills/relsa-severity-assessment) — Multivariate severity assessment and humane endpoint prediction for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-ba… * [`scientific-brainstorming`](/research-agent-skills/skills/scientific-brainstorming) — Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial re… * [`statistical-power`](/research-agent-skills/skills/statistical-power) — Sample-size and statistical power calculations for planning studies. * [`uncertainty-and-units`](/research-agent-skills/skills/uncertainty-and-units) — Track physical units and propagate measurement uncertainty in scientific calculations using pint and uncertainties. ## data-science-and-ml Data analysis, statistics and machine learning libraries. * [`aeon`](/research-agent-skills/skills/aeon) — This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation… * [`dask`](/research-agent-skills/skills/dask) — Distributed computing for larger-than-RAM pandas/NumPy workflows. * [`datalad`](/research-agent-skills/skills/datalad) — Retrieve, version, and publish scientific datasets with DataLad and git-annex, and capture computational provenance with datalad run, rerun, and containers-run. * [`exploratory-data-analysis`](/research-agent-skills/skills/exploratory-data-analysis) — Perform bounded, local exploratory analysis of explicitly supported scientific files. * [`get-available-resources`](/research-agent-skills/skills/get-available-resources) — Detect host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a cl… * [`hugging-science`](/research-agent-skills/skills/hugging-science) — Use when the user is doing AI/ML work in a scientific domain such as biology, chemistry, physics, astronomy, climate, genomics, materials, medicine, ecology, e… * [`lamindb`](/research-agent-skills/skills/lamindb) — Use when working with LaminDB, the open-source lineage-native lakehouse for biological datasets and models. * [`matlab`](/research-agent-skills/skills/matlab) — Designs, reviews, and migrates MATLAB R2026a and GNU Octave numerical code, covering functions with arguments blocks, arrays and indexing, tables and timetable… * [`modal`](/research-agent-skills/skills/modal) — Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. * [`networkx`](/research-agent-skills/skills/networkx) — Create, analyze, and visualize complex networks and graphs in Python with NetworkX. * [`optimize-for-gpu`](/research-agent-skills/skills/optimize-for-gpu) — GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. * [`polars`](/research-agent-skills/skills/polars) — High-performance DataFrame library for Python ETL, analytics, and pandas migration. * [`pufferlib`](/research-agent-skills/skills/pufferlib) — Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review. * [`pymc`](/research-agent-skills/skills/pymc) — Builds, fits, checks, and compares Bayesian models in Python with PyMC and ArviZ. * [`pymoo`](/research-agent-skills/skills/pymoo) — Solves single- and multi-objective optimization problems in Python with pymoo, using NSGA-II, NSGA-III, MOEA/D, SPEA2, RVEA, GA, DE and PSO. * [`pytorch-lightning`](/research-agent-skills/skills/pytorch-lightning) — Organizes PyTorch training code with the lightning package (PyTorch Lightning): LightningModule, LightningDataModule, Trainer, callbacks such as ModelCheckpoin… * [`scikit-learn`](/research-agent-skills/skills/scikit-learn) — Covers classical machine learning in Python with scikit-learn (sklearn): classification and regression estimators, clustering and dimensionality reduction, pre… * [`scikit-survival`](/research-agent-skills/skills/scikit-survival) — Builds, evaluates, and audits right-censored survival analysis workflows with scikit-survival (sksurv): Cox PH, Coxnet, IPC ridge, survival trees, forests, boo… * [`shap`](/research-agent-skills/skills/shap) — Explain and audit machine-learning predictions with SHAP. * [`simpy`](/research-agent-skills/skills/simpy) — Builds, tests, and analyzes bounded process-based discrete-event simulations in Python with SimPy 4.1.2: Environment, Timeout, Process, AnyOf/AllOf conditions,… * [`stable-baselines3`](/research-agent-skills/skills/stable-baselines3) — Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. * [`statistical-analysis`](/research-agent-skills/skills/statistical-analysis) — Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted rep… * [`statsmodels`](/research-agent-skills/skills/statsmodels) — Statistical models library for Python. * [`sympy`](/research-agent-skills/skills/sympy) — Use when you need exact symbolic math in Python — algebra, calculus, equation solving, symbolic linear algebra, or code generation via lambdify/LaTeX. * [`timesfm-forecasting`](/research-agent-skills/skills/timesfm-forecasting) — Zero-shot time series forecasting with Google's TimesFM foundation model. * [`torch-geometric`](/research-agent-skills/skills/torch-geometric) — PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor… * [`transformers`](/research-agent-skills/skills/transformers) — Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal ta… * [`umap-learn`](/research-agent-skills/skills/umap-learn) — Reduces and embeds high-dimensional data with umap-learn (UMAP) in Python, including 2D/3D visualization, supervised and semi-supervised UMAP, DensMAP, Aligned… * [`vaex`](/research-agent-skills/skills/vaex) — Processes and analyzes tabular datasets too large for RAM using Vaex, a Python library for lazy, out-of-core DataFrames over memory-mapped HDF5 and Arrow files… * [`zarr-python`](/research-agent-skills/skills/zarr-python) — Guides use of Zarr-Python 3 for storing chunked, compressed N-dimensional arrays and groups, with local, in-memory, ZIP, and fsspec-backed S3/GCS/HTTP stores,… ## visualization-and-presentation Figures, schematics, posters, slides and talks. * [`academic-plotting`](/research-agent-skills/skills/academic-plotting) — Generates publication-quality figures for ML papers from research context. * [`generate-image`](/research-agent-skills/skills/generate-image) — Generate or edit images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). * [`infographics`](/research-agent-skills/skills/infographics) — Generates infographics from natural-language prompts using Nano Banana Pro image generation, with optional Perplexity Sonar research for facts and a Gemini 3.6… * [`latex-posters`](/research-agent-skills/skills/latex-posters) — Creates research posters in LaTeX with beamerposter, tikzposter, or baposter, covering page sizes (A0, A1, 36x48 inch), multi-column layouts, color schemes, fi… * [`matplotlib`](/research-agent-skills/skills/matplotlib) — Low-level plotting library for full customization. * [`pptx-posters`](/research-agent-skills/skills/pptx-posters) — Create and audit editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. * [`presenting-conference-talks`](/research-agent-skills/skills/presenting-conference-talks) — Generates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. * [`scientific-schematics`](/research-agent-skills/skills/scientific-schematics) — Generates publication-style scientific diagrams as raster PNG images from a natural-language prompt, using Nano Banana 2 via OpenRouter, then scores each image… * [`scientific-slides`](/research-agent-skills/skills/scientific-slides) — Build slide decks and presentations for research talks. * [`scientific-visualization`](/research-agent-skills/skills/scientific-visualization) — Create and audit truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. * [`seaborn`](/research-agent-skills/skills/seaborn) — Statistical visualization with pandas integration. ## knowledge-and-rag Vector databases, embeddings, RAG and knowledge graphs over research corpora. * [`chroma`](/research-agent-skills/skills/chroma) — Open-source embedding database for AI applications. * [`faiss`](/research-agent-skills/skills/faiss) — Facebook's library for efficient similarity search and clustering of dense vectors. * [`paper-corpus-rag`](/research-agent-skills/skills/paper-corpus-rag) — Build grounded question answering and retrieval-augmented generation (RAG) over your own collection of research papers, with answers that cite the exact paper… * [`pinecone`](/research-agent-skills/skills/pinecone) — Guides use of Pinecone, a managed serverless vector database, through its Python client and the LangChain and LlamaIndex integrations. * [`qdrant-vector-search`](/research-agent-skills/skills/qdrant-vector-search) — High-performance vector similarity search engine for RAG and semantic search. * [`research-knowledge-graph`](/research-agent-skills/skills/research-knowledge-graph) — Turn a bibliography or literature corpus into a knowledge graph of papers, authors, venues, topics and citation links, then analyze it (citation clusters, key… * [`sentence-transformers`](/research-agent-skills/skills/sentence-transformers) — Generates sentence, text, and image embeddings locally with the Python sentence-transformers (SBERT) library, using pre-trained Hugging Face models such as all… ## scientific-databases Programmatic access to public scientific databases and APIs. * [`bioservices`](/research-agent-skills/skills/bioservices) — Unified Python interface to 40+ bioinformatics services. * [`cellxgene-census`](/research-agent-skills/skills/cellxgene-census) — Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. * [`database-lookup`](/research-agent-skills/skills/database-lookup) — Query documented public database APIs with explicit endpoints, filters, pagination, and provenance. * [`depmap`](/research-agent-skills/skills/depmap) — Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. * [`genomic-coordinates`](/research-agent-skills/skills/genomic-coordinates) — Convert genomic intervals between coordinate conventions, normalise and compare variant representations, and detect assembly or contig-naming mismatches before… * [`gget`](/research-agent-skills/skills/gget) — Queries 20+ bioinformatics databases and analysis services through the gget CLI and Python package, covering Ensembl gene search, info and sequences (ref, sear… * [`imaging-data-commons`](/research-agent-skills/skills/imaging-data-commons) — Query and download public cancer imaging data from NCI Imaging Data Commons. * [`ncats-arax`](/research-agent-skills/skills/ncats-arax) — Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationshi… * [`onekgpd`](/research-agent-skills/skills/onekgpd) — Query the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. * [`ontology-term-resolution`](/research-agent-skills/skills/ontology-term-resolution) — Resolve free-text scientific labels to ontology term IDs and validate existing CURIEs against the EBI Ontology Lookup Service (OLS4). * [`pytdc`](/research-agent-skills/skills/pytdc) — Uses the PyTDC package (import tdc, Therapeutics Data Commons) to discover therapeutic ML tasks from tdc.metadata, plan and load approved datasets, apply task-… * [`usfiscaldata`](/research-agent-skills/skills/usfiscaldata) — Query the U.S. ## life-sciences Genomics, single-cell, proteomics, neuroscience and systems biology. * [`13c-metabolic-flux`](/research-agent-skills/skills/13c-metabolic-flux) — Estimates intracellular metabolic fluxes from steady-state carbon-13 isotope-tracing measurements using validated atom maps, mfapy isotope simulation, constrai… * [`alphagenome`](/research-agent-skills/skills/alphagenome) — Look up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and qua… * [`anndata`](/research-agent-skills/skills/anndata) — Data structure for annotated matrices in single-cell analysis. * [`arboreto`](/research-agent-skills/skills/arboreto) — Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). * [`bids`](/research-agent-skills/skills/bids) — Organizes, queries, validates, and converts neuroscience and biomedical datasets using the Brain Imaging Data Structure (BIDS) standard, covering MRI, PET, EEG… * [`biopython`](/research-agent-skills/skills/biopython) — Provides Biopython (Bio.Seq, Bio.SeqIO, Bio.Align, Bio.Entrez, Bio.Blast, Bio.PDB, Bio.Phylo, Bio.motifs, Bio.SeqUtils, Bio.Restriction) for sequence handling,… * [`bulk-rnaseq`](/research-agent-skills/skills/bulk-rnaseq) — End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, f… * [`cobrapy`](/research-agent-skills/skills/cobrapy) — Runs constraint-based metabolic modeling with COBRApy (Python, import cobra) on genome-scale models in SBML, JSON, YAML, or MATLAB format. * [`deeptools`](/research-agent-skills/skills/deeptools) — Runs deepTools command-line programs on NGS alignment data: bamCoverage and bamCompare for BAM to bigWig/bedGraph with RPGC, CPM, RPKM or BPM normalization, mu… * [`esm`](/research-agent-skills/skills/esm) — Covers the EvolutionaryScale/Biohub `esm` Python SDK: ESM3 generative protein design (sequence, structure and function tracks, chain-of-thought), ESMC embeddin… * [`etetoolkit`](/research-agent-skills/skills/etetoolkit) — Analyze, manipulate, compare, annotate, and visualize phylogenetic or other hierarchical trees with ETE 4. * [`flowio`](/research-agent-skills/skills/flowio) — Read, inspect, and write Flow Cytometry Standard (FCS) 2.0, 3.0, and 3.1 files with FlowIO. * [`folklore-variant-evidence`](/research-agent-skills/skills/folklore-variant-evidence) — Retrieve ClinGen gene-disease validity assertions for a public gene or disease, and review source-linked public evidence and literature for one supported GRCh3… * [`geniml`](/research-agent-skills/skills/geniml) — Plans and audits local genomic-interval machine learning workflows with Geniml (0.8.4) and Gtars: validates BED files against chromosome sizes and assembly con… * [`genomic-intelligence`](/research-agent-skills/skills/genomic-intelligence) — Predict regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no… * [`gtars`](/research-agent-skills/skills/gtars) — Inspects and plans work with Gtars, the Rust/Python/CLI toolkit for genomic intervals: BED RegionSet set algebra (reduce, setdiff, intersect, closest, cluster,… * [`matchms`](/research-agent-skills/skills/matchms) — Process, clean, compare, and search tandem mass spectra with matchms. * [`neurokit2`](/research-agent-skills/skills/neurokit2) — Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, var… * [`neuropixels-analysis`](/research-agent-skills/skills/neuropixels-analysis) — Analyze Neuropixels extracellular recordings end-to-end with SpikeInterface. * [`nextflow`](/research-agent-skills/skills/nextflow) — Build, run, and debug Nextflow data pipelines and nf-core workflows end to end. * [`pacsomatic`](/research-agent-skills/skills/pacsomatic) — Operator toolkit for nf-core/pacsomatic matched tumor-normal workflows from BAM inputs. * [`pathogen-variant-surveillance`](/research-agent-skills/skills/pathogen-variant-surveillance) — Query live pathogen genomic surveillance data through the GenSpectrum LAPIS API to find which viral lineages are circulating now, how fast they are growing, an… * [`pathway-enrichment`](/research-agent-skills/skills/pathway-enrichment) — Run pathway and gene-set enrichment analysis on gene lists or ranked gene data, then interpret the results. * [`polars-bio`](/research-agent-skills/skills/polars-bio) — Python library polars-bio for genomic interval operations and bioinformatics file I/O on Polars DataFrames, built on Arrow and DataFusion. * [`pydeseq2`](/research-agent-skills/skills/pydeseq2) — Runs differential expression analysis on bulk RNA-seq count data with PyDESeq2, the Python port of DESeq2. * [`pyopenms`](/research-agent-skills/skills/pyopenms) — Complete mass spectrometry analysis platform. * [`pysam`](/research-agent-skills/skills/pysam) — Python/HTSlib workflows for genomic files. * [`scanpy`](/research-agent-skills/skills/scanpy) — Standard single-cell RNA-seq analysis pipeline. * [`scikit-bio`](/research-agent-skills/skills/scikit-bio) — Python library scikit-bio for biological sequence and community-ecology analysis: DNA/RNA/protein sequences, pair\_align alignment, phylogenetic trees (NJ, UPGM… * [`scvelo`](/research-agent-skills/skills/scvelo) — Performs RNA velocity analysis with scVelo on single-cell RNA-seq AnnData objects that have spliced and unspliced layers (from velocyto, STARsolo, kallisto|bus… * [`scvi-tools`](/research-agent-skills/skills/scvi-tools) — Trains and applies scvi-tools probabilistic deep generative models (scVI, scANVI, totalVI, MultiVI, PeakVI, DestVI, Solo, CellAssign, MrVI and others) on AnnDa… * [`tiledbvcf`](/research-agent-skills/skills/tiledbvcf) — Stores and queries genomic variant data in TileDB-VCF datasets using the tiledbvcf Python API and CLI (create, store, export, list, stat). * [`waypoint-bio`](/research-agent-skills/skills/waypoint-bio) — Use when working with Outpost Bio's open microbiome foundation models - the Waypoint checkpoints (Waypoint-6m, Waypoint-45m, Waypoint-170m), the Atlas pretrain… ## chemistry-and-drug-discovery Cheminformatics, molecular modelling, protein design and pharmacology. * [`adaptyv`](/research-agent-skills/skills/adaptyv) — How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. * [`datamol`](/research-agent-skills/skills/datamol) — Wraps RDKit through the datamol Python library (import datamol as dm) for molecular cheminformatics, returning native rdkit.Chem.Mol objects. * [`deepchem`](/research-agent-skills/skills/deepchem) — Molecular ML with diverse featurizers and pre-built datasets. * [`diffdock`](/research-agent-skills/skills/diffdock) — DiffDock and DiffDock-L molecular docking. * [`medchem`](/research-agent-skills/skills/medchem) — Filters and triages small-molecule libraries with the Python medchem library (datamol-io, v2.0.5) on top of RDKit and datamol. * [`molecular-dynamics`](/research-agent-skills/skills/molecular-dynamics) — Runs and analyzes molecular dynamics simulations using OpenMM and MDAnalysis. * [`molfeat`](/research-agent-skills/skills/molfeat) — Converts SMILES strings or RDKit/datamol molecules into numerical features using molfeat (0.11.0), which provides calculators, scikit-learn compatible transfor… * [`pkpd-modeling`](/research-agent-skills/skills/pkpd-modeling) — Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD,… * [`rdkit`](/research-agent-skills/skills/rdkit) — Guides use of RDKit (Python) for reading and writing SMILES, MOL/SDF, and InChI, computing descriptors (MW, LogP, TPSA), generating Morgan/MACCS/atom-pair fing… * [`rowan`](/research-agent-skills/skills/rowan) — Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. * [`tamarind`](/research-agent-skills/skills/tamarind) — Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs r… * [`torchdrug`](/research-agent-skills/skills/torchdrug) — Build and troubleshoot TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, p… ## clinical-and-health Clinical research, medical imaging, pathology and health data. * [`clinical-decision-support`](/research-agent-skills/skills/clinical-decision-support) — Prepare and validate research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. * [`clinical-reports`](/research-agent-skills/skills/clinical-reports) — Generates fail-closed draft JSON templates and runs local deterministic structure and consistency checks for clinical reports: CARE case reports, radiology, pa… * [`histolab`](/research-agent-skills/skills/histolab) — Extracts tiles and preprocesses H\&E whole slide images with the histolab Python library (OpenSlide), covering slide inspection, tissue masks (TissueMask, Bigge… * [`pathml`](/research-agent-skills/skills/pathml) — Covers local, research-only computational pathology with PathML 3.0.5: loading and tiling whole-slide images (OpenSlide, Bio-Formats), preprocessing and QC pip… * [`pydicom`](/research-agent-skills/skills/pydicom) — Reads, inspects, writes, and transforms local DICOM files with pydicom 3.x (dcmread, dcmwrite, pydicom.pixels), including metadata, transfer syntaxes, compress… * [`pyhealth`](/research-agent-skills/skills/pyhealth) — Builds clinical deep-learning pipelines with PyHealth using its Dataset → Task → Model → Trainer → Metrics pattern. * [`treatment-plans`](/research-agent-skills/skills/treatment-plans) — Format and structurally validate local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed pro… ## physical-sciences Physics, astronomy, quantum computing, materials and earth science. * [`astropy`](/research-agent-skills/skills/astropy) — Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, W… * [`cirq`](/research-agent-skills/skills/cirq) — Google quantum computing framework. * [`fluidsim`](/research-agent-skills/skills/fluidsim) — Plan, configure, inspect, restart, and analyze bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. * [`geomaster`](/research-agent-skills/skills/geomaster) — Provides geospatial and Earth observation workflows using GeoPandas, Rasterio, GDAL, Xarray, Shapely, Laspy, PDAL, Google Earth Engine, and STAC/Planetary Comp… * [`geopandas`](/research-agent-skills/skills/geopandas) — Guidance and local audit CLIs for Python workflows using GeoPandas 1.1.4 GeoSeries and GeoDataFrame for planar vector data: CRS handling, geometry validity and… * [`openpiv`](/research-agent-skills/skills/openpiv) — Particle Image Velocimetry (PIV) analysis with OpenPIV. * [`pennylane`](/research-agent-skills/skills/pennylane) — Hardware-agnostic quantum ML framework with automatic differentiation. * [`pymatgen`](/research-agent-skills/skills/pymatgen) — Analyzes, validates, converts, and transforms crystal structures and molecules with pymatgen. * [`qiskit`](/research-agent-skills/skills/qiskit) — Build, simulate, transpile, and execute quantum circuits with Qiskit and IBM Quantum Runtime. * [`qutip`](/research-agent-skills/skills/qutip) — Simulate and audit closed and open quantum-system models with QuTiP 5, including deterministic, trajectory, steady-state, spectral, and phase-space workflows. ## lab-automation Lab platforms, ELNs, liquid handlers and manufacturing integrations. * [`benchling-integration`](/research-agent-skills/skills/benchling-integration) — Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. * [`dnanexus-integration`](/research-agent-skills/skills/dnanexus-integration) — Build and operate reproducible genomics workloads on DNAnexus with the dx CLI, dxpy, apps/applets, native workflows, dxCompiler, and Nextflow. * [`fictiv`](/research-agent-skills/skills/fictiv) — Drives the Fictiv on-demand manufacturing web app (app.fictiv.com) in the user's browser, since there is no public API. * [`ginkgo-cloud-lab`](/research-agent-skills/skills/ginkgo-cloud-lab) — Submit and manage protocols on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio), a web-based interface for autonomous lab execution on Reconfigurable Automation Ca… * [`lab-hardware-cad`](/research-agent-skills/skills/lab-hardware-cad) — Design custom laboratory hardware as parametric build123d models and export fabrication-ready STEP, STL, and DXF files - microfluidic chips and molds, optomech… * [`labarchive-integration`](/research-agent-skills/skills/labarchive-integration) — Securely integrate with the official LabArchives ELN REST-like API and Inventory API v1. * [`latchbio-integration`](/research-agent-skills/skills/latchbio-integration) — Build, register, debug, and operate bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic exe… * [`omero-integration`](/research-agent-skills/skills/omero-integration) — Securely inspect and automate microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and… * [`opentrons-integration`](/research-agent-skills/skills/opentrons-integration) — Author, review, migrate, simulate, and troubleshoot official Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots. * [`protocolsio-integration`](/research-agent-skills/skills/protocolsio-integration) — Reads, validates, and exports protocols.io data using the documented REST v3/v4 endpoints and the official MCP endpoint, and builds non-executing mutation plan… * [`pylabrobot`](/research-agent-skills/skills/pylabrobot) — Develop and review PyLabRobot lab-automation resources, liquid-handling plans, offline simulations, and supported-device integrations. ## research-automation Autonomous research loops, agent harnesses and research artifacts. * [`ara-compiler`](/research-agent-skills/skills/ara-compiler) — Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact… * [`ara-research-manager`](/research-agent-skills/skills/ara-research-manager) — Records research provenance at the end of a coding or research session by scanning the conversation and writing decisions, experiments, dead ends, pivots, clai… * [`ara-rigor-reviewer`](/research-agent-skills/skills/ara-rigor-reviewer) — Performs ARA Seal Level 2 semantic epistemic review of an Agent-Native Research Artifact directory, reading PAPER.md, logic/claims.md, logic/experiments.md, an… * [`arbor`](/research-agent-skills/skills/arbor) — Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree… * [`autoresearch`](/research-agent-skills/skills/autoresearch) — Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. * [`autoskill`](/research-agent-skills/skills/autoskill) — Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing research-agent-skills, and draft new skills (or compo… * [`pi-agent`](/research-agent-skills/skills/pi-agent) — Build with and use Pi, the minimal terminal coding harness. * [`research-agent-skills`](/research-agent-skills/skills/research-agent-skills) — Navigate the Research Agent Skills collection by Kalaris Labs for academia across AI, machine learning, biology, chemistry, medicine, physics, and academic wri… * [`research-skill-creator`](/research-agent-skills/skills/research-skill-creator) — Create, improve and test agent skills for research workflows (paper writing, lab protocols, analysis pipelines, domain databases) that meet the Agent Skills sp… ## ml-training Model architectures, tokenization, fine-tuning, post-training, distributed training, optimization. * [`awq-quantization`](/research-agent-skills/skills/awq-quantization) — Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. * [`axolotl`](/research-agent-skills/skills/axolotl) — Provides guidance for fine-tuning large language models with Axolotl, covering YAML training configs, LoRA and QLoRA, preference training with DPO, KTO, ORPO a… * [`deepspeed`](/research-agent-skills/skills/deepspeed) — Covers DeepSpeed for distributed deep learning training and I/O: ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8 training, 1-bit Adam, sparse att… * [`distributed-llm-pretraining-torchtitan`](/research-agent-skills/skills/distributed-llm-pretraining-torchtitan) — Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). * [`fine-tuning-with-trl`](/research-agent-skills/skills/fine-tuning-with-trl) — Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward m… * [`gguf-quantization`](/research-agent-skills/skills/gguf-quantization) — GGUF format and llama.cpp quantization for efficient CPU/GPU inference. * [`gptq`](/research-agent-skills/skills/gptq) — Quantizes LLMs to 4-bit (also 3-bit) with GPTQ using group-wise quantization (group size 128 by default), via AutoGPTQ and transformers. * [`grpo-rl-training`](/research-agent-skills/skills/grpo-rl-training) — Guides GRPO (Group Relative Policy Optimization) fine-tuning of language models with the TRL library, including GRPOTrainer configuration, composing multiple r… * [`hqq-quantization`](/research-agent-skills/skills/hqq-quantization) — Half-Quadratic Quantization for LLMs without calibration data. * [`huggingface-accelerate`](/research-agent-skills/skills/huggingface-accelerate) — Wraps existing PyTorch training scripts with HuggingFace Accelerate (Accelerator class, accelerate config, accelerate launch) so the same code runs on CPU, sin… * [`huggingface-tokenizers`](/research-agent-skills/skills/huggingface-tokenizers) — Provides the HuggingFace Tokenizers library (Rust core with Python and Node.js bindings) for training and using BPE, WordPiece, and Unigram tokenizers. * [`implementing-llms-litgpt`](/research-agent-skills/skills/implementing-llms-litgpt) — Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). * [`llama-factory`](/research-agent-skills/skills/llama-factory) — Guides fine-tuning of large language models with LLaMA-Factory, covering the WebUI no-code interface, training across 100+ supported models, quantized QLoRA at… * [`mamba-architecture`](/research-agent-skills/skills/mamba-architecture) — Explains how to use Mamba selective state-space models (state-spaces/mamba package, Mamba-1 with d\_state=16 and Mamba-2 with multi-head structure and d\_state=1… * [`miles-rl-training`](/research-agent-skills/skills/miles-rl-training) — Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. * [`ml-training-recipes`](/research-agent-skills/skills/ml-training-recipes) — Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. * [`nanogpt`](/research-agent-skills/skills/nanogpt) — Provides nanoGPT, Karpathy's minimal PyTorch GPT implementation (model.py and train.py), with workflows for training character-level Shakespeare on CPU, reprod… * [`openrlhf-training`](/research-agent-skills/skills/openrlhf-training) — High-performance RLHF framework with Ray+vLLM acceleration. * [`optimizing-attention-flash`](/research-agent-skills/skills/optimizing-attention-flash) — Enables Flash Attention for transformer models using PyTorch native scaled\_dot\_product\_attention (PyTorch 2.2+) or the flash-attn library, including multi-quer… * [`peft-fine-tuning`](/research-agent-skills/skills/peft-fine-tuning) — Fine-tunes LLMs with Hugging Face PEFT, using LoRA, QLoRA, IA3, AdaLoRA, prefix tuning, and prompt tuning so that under 1% of parameters are trained. * [`pytorch-fsdp2`](/research-agent-skills/skills/pytorch-fsdp2) — Adds PyTorch FSDP2 (fully\_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. * [`pytorch-lightning-distributed`](/research-agent-skills/skills/pytorch-lightning-distributed) — High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. * [`quantizing-models-bitsandbytes`](/research-agent-skills/skills/quantizing-models-bitsandbytes) — Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. * [`ray-train`](/research-agent-skills/skills/ray-train) — Distributed training orchestration across clusters. * [`rwkv-architecture`](/research-agent-skills/skills/rwkv-architecture) — Covers the RWKV (Receptance Weighted Key Value) architecture, an RNN/Transformer hybrid with O(n) inference and no KV cache, including RWKV-7, its parallel GPT… * [`sentencepiece`](/research-agent-skills/skills/sentencepiece) — Language-independent tokenizer treating text as raw Unicode. * [`simpo-training`](/research-agent-skills/skills/simpo-training) — Simple Preference Optimization for LLM alignment. * [`slime-rl-training`](/research-agent-skills/skills/slime-rl-training) — Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. * [`torchforge-rl-training`](/research-agent-skills/skills/torchforge-rl-training) — Provides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms. * [`training-llms-megatron`](/research-agent-skills/skills/training-llms-megatron) — Trains large language models (2B-462B parameters) with NVIDIA Megatron-Core using tensor, pipeline, sequence, context, and expert parallelism, plus FP8 on H100… * [`unsloth`](/research-agent-skills/skills/unsloth) — Provides guidance on fine-tuning large language models with Unsloth, a library for faster, lower-memory training using LoRA and QLoRA, based on its official do… * [`verl-rl-training`](/research-agent-skills/skills/verl-rl-training) — Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). ## ml-evaluation-and-safety Evaluation harnesses, interpretability and safety/alignment. * [`constitutional-ai`](/research-agent-skills/skills/constitutional-ai) — Anthropic's method for training harmless AI through self-improvement. * [`evaluating-code-models`](/research-agent-skills/skills/evaluating-code-models) — Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass\@k metrics. * [`evaluating-llms-harness`](/research-agent-skills/skills/evaluating-llms-harness) — Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). * [`llamaguard`](/research-agent-skills/skills/llamaguard) — Classifies LLM prompts and responses as safe or unsafe using Meta's LlamaGuard (7B v1, 8B v2 and v3) across six categories: violence and hate, sexual content,… * [`nemo-evaluator-sdk`](/research-agent-skills/skills/nemo-evaluator-sdk) — Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. * [`nemo-guardrails`](/research-agent-skills/skills/nemo-guardrails) — Adds runtime safety rails to LLM applications with NVIDIA NeMo Guardrails, configured through Colang 2.0 flows. * [`nnsight-remote-interpretability`](/research-agent-skills/skills/nnsight-remote-interpretability) — Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. * [`prompt-guard`](/research-agent-skills/skills/prompt-guard) — Classifies text with Meta's Prompt Guard, an 86M-parameter model loaded from HuggingFace, into BENIGN, INJECTION or JAILBREAK labels to detect prompt injection… * [`pyvene-interventions`](/research-agent-skills/skills/pyvene-interventions) — Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. * [`sparse-autoencoder-training`](/research-agent-skills/skills/sparse-autoencoder-training) — Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. * [`transformer-lens-interpretability`](/research-agent-skills/skills/transformer-lens-interpretability) — Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation… ## ml-inference-and-ops Inference serving, GPU infrastructure, MLOps and observability. * [`experiment-tracking-swanlab`](/research-agent-skills/skills/experiment-tracking-swanlab) — Tracks ML experiments with SwanLab, an open-source tool covering swanlab.init, config and metric logging, scalar charts, and media logging (images, audio, text… * [`lambda-labs-gpu-cloud`](/research-agent-skills/skills/lambda-labs-gpu-cloud) — Reserved and on-demand GPU cloud instances for ML training and inference. * [`langsmith-observability`](/research-agent-skills/skills/langsmith-observability) — LLM observability platform for tracing, evaluation, and monitoring. * [`llama-cpp`](/research-agent-skills/skills/llama-cpp) — Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. * [`mlflow`](/research-agent-skills/skills/mlflow) — Tracks machine learning experiments and manages model lifecycles with MLflow, covering mlflow\.log\_param, log\_metric and log\_artifact, autologging for scikit-le… * [`modal-serverless-gpu`](/research-agent-skills/skills/modal-serverless-gpu) — Serverless GPU cloud platform for running ML workloads. * [`phoenix-observability`](/research-agent-skills/skills/phoenix-observability) — Open-source AI observability platform for LLM tracing, evaluation, and monitoring. * [`serving-llms-vllm`](/research-agent-skills/skills/serving-llms-vllm) — Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. * [`sglang`](/research-agent-skills/skills/sglang) — Fast structured generation and serving for LLMs with RadixAttention prefix caching. * [`skypilot-multi-cloud-orchestration`](/research-agent-skills/skills/skypilot-multi-cloud-orchestration) — Multi-cloud orchestration for ML workloads with automatic cost optimization. * [`tensorboard`](/research-agent-skills/skills/tensorboard) — Logs and views ML training data in TensorBoard using PyTorch SummaryWriter and TensorFlow/Keras callbacks: scalars, images, text, histograms, model graphs, emb… * [`tensorrt-llm`](/research-agent-skills/skills/tensorrt-llm) — Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. * [`weights-and-biases`](/research-agent-skills/skills/weights-and-biases) — Logs and tracks machine learning experiments with Weights & Biases (W\&B, wandb): metrics, hyperparameters, checkpoints, sweeps, artifacts with lineage, model r… ## llm-applications Agent frameworks, prompt engineering and structured generation. * [`autogpt-agents`](/research-agent-skills/skills/autogpt-agents) — Autonomous AI agent platform for building and deploying continuous agents. * [`crewai-multi-agent`](/research-agent-skills/skills/crewai-multi-agent) — Multi-agent orchestration framework for autonomous AI collaboration. * [`dspy`](/research-agent-skills/skills/dspy) — Builds and optimizes language model programs with DSPy (Stanford NLP), using Signatures, modules (Predict, ChainOfThought, ReAct, ProgramOfThought) and optimiz… * [`evolving-ai-agents`](/research-agent-skills/skills/evolving-ai-agents) — Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. * [`guidance`](/research-agent-skills/skills/guidance) — Constrains LLM output during generation with Guidance (Microsoft Research), using regex, select() choices, context-free grammars, token healing, and @guidance… * [`instructor`](/research-agent-skills/skills/instructor) — Extracts structured, validated data from LLM responses using the Instructor Python library with Pydantic response models, including nested models, enums, custo… * [`langchain`](/research-agent-skills/skills/langchain) — Framework for building LLM-powered applications with agents, chains, and RAG. * [`llamaindex`](/research-agent-skills/skills/llamaindex) — Data framework for building LLM applications with RAG. * [`outlines`](/research-agent-skills/skills/outlines) — Generates guaranteed-valid structured output from LLMs with Outlines (dottxt.ai), constraining token sampling via finite state machines for JSON schemas, Pydan… ## multimodal-and-emerging Vision, audio, robotics, data processing and emerging techniques. * [`audiocraft-audio-generation`](/research-agent-skills/skills/audiocraft-audio-generation) — PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). * [`blip-2-vision-language`](/research-agent-skills/skills/blip-2-vision-language) — Explains how to use Salesforce BLIP-2 (Q-Former bridging a frozen image encoder and an LLM such as OPT or FlanT5) through HuggingFace Transformers and LAVIS fo… * [`clip`](/research-agent-skills/skills/clip) — OpenAI's model connecting vision and language. * [`evaluating-cosmos-policy`](/research-agent-skills/skills/evaluating-cosmos-policy) — Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. * [`fine-tuning-openvla-oft`](/research-agent-skills/skills/fine-tuning-openvla-oft) — Fine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning… * [`fine-tuning-serving-openpi`](/research-agent-skills/skills/fine-tuning-serving-openpi) — Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, an… * [`knowledge-distillation`](/research-agent-skills/skills/knowledge-distillation) — Compress large language models using knowledge distillation from teacher to student models. * [`llava`](/research-agent-skills/skills/llava) — Large Language and Vision Assistant. * [`long-context`](/research-agent-skills/skills/long-context) — Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. * [`model-merging`](/research-agent-skills/skills/model-merging) — Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. * [`model-pruning`](/research-agent-skills/skills/model-pruning) — Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. * [`moe-training`](/research-agent-skills/skills/moe-training) — Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. * [`nemo-curator`](/research-agent-skills/skills/nemo-curator) — GPU-accelerated data curation for LLM training. * [`ray-data`](/research-agent-skills/skills/ray-data) — Scalable data processing for ML workloads. * [`segment-anything-model`](/research-agent-skills/skills/segment-anything-model) — Foundation model for image segmentation with zero-shot transfer. * [`speculative-decoding`](/research-agent-skills/skills/speculative-decoding) — Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. * [`stable-diffusion-image-generation`](/research-agent-skills/skills/stable-diffusion-image-generation) — Generates images with Stable Diffusion models (SD 1.5, SDXL, SD 3.0, Flux) through the HuggingFace Diffusers library, covering text-to-image, image-to-image, i… * [`whisper`](/research-agent-skills/skills/whisper) — Transcribes and translates audio with OpenAI's Whisper (openai-whisper Python package and whisper CLI), covering model sizes from tiny to large plus turbo, lan… This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.