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digital-health-clinical-asr-evalnvidia1.9KStage 3 of Clinical ASR Flywheel. Score a NeMo manifest, produce the five-section KER leaderboard (by-ipa_source diagnostic). Not for ASR auth (/riva-asr).unibind-databasegoogle-deepmind1.9KQueries the UniBind database for experimentally validated transcription factor (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets, downloading binding site coordinates (BED/FASTA) for local analysis, or listing available datasets by species, cell line, or TF name. Don't use to query specific intervals, locations, genes, motif models or expression data.data-analysislingzhi2271.9KGenerate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper.earth2studio-discovernvidia1.9KFind Earth2Studio models, data sources, and examples for a weather/climate use case. Do NOT use for writing inference code, downloading data, or installation.vss-generate-video-reportnvidia1.9KUse this skill when producing a VSS analysis report — Mode A per-clip VLM, Mode B incident-range via video-analytics. Not for standalone video summarization, real-time alerts or ad-hoc Q&A.dicom-series-to-volumenvidia1.8KUsed for converting one CT DICOM series folder to a HU NIfTI volume with affine evidence. Not for multi-frame DICOM or clinical use.earth2studio-data-fetchnvidia1.8KFetch weather/climate data via Earth2Studio data sources for specific variables and times. Do NOT use for inference pipelines, model discovery, or installation.earth2studio-deterministic-forecastnvidia1.8KBuild deterministic forecast scripts with Earth2Studio (model, data source, IO, inference). Do NOT use for ensemble, diagnostics, data-only fetch, or install.exploratory-data-analysisk-dense-ai1.8KPerform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.finlabkoreal68031.8KComprehensive guide for FinLab quantitative trading package for Taiwan stock market (台股). Use when working with trading strategies, backtesting, Taiwan stock data, FinLabDataFrame, factor analysis, stock selection, or when the user mentions FinLab, trading, 回測, 策略, 台股, quant trading, or stock market analysis. Includes data access, strategy development, backtesting workflows, and best practices.layers-observed-behaviourjamiemill1.8KTechniques for planning user research and synthesising it into grounded, confidence-rated findings about what users actually dodig-through-data-brokersuseosint1.8KUse people-search aggregators and primary public records to find addresses, phone numbers, relatives, age and background on a person, and to audit and remove your own exposure. Covers Spokeo, BeenVerified, Whitepages, TruePeopleSearch, FastPeopleSearch, That'sThem, Radaris, Intelius and Pipl, plus voter files and county court and property records. Use when running a people search or reverse address lookup, tracing a debtor or missing person, building a subject's address history, or removing your_referencesjihe5201.8K共享规范知识库。包含数学建模竞赛的写作规范、题型防错速查、图表规范等参考内容。其他 skills 在执行过程中按需读取，无需单独触发。usability-test-planowl-listener1.8KDesign a usability study — research questions, methodology, participant criteria, metrics, and facilitation guide. Use when planning the study as a whole. For writing the task scenarios inside it, use `test-scenario` (prototyping-testing).baidu-searchcountbot-ai1.8Kstatsmodelsk-dense-ai1.8KStatistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.seabornk-dense-ai1.8KStatistical 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.backward-traceabilitylingzhi2271.8KMake every number in the final PDF traceable to the exact code line that produced it. Uses \hypertarget/\hyperlink LaTeX commands and \num{formula} evaluated at compile time. Use for reproducibility and data integrity verification.hypothesis-generationk-dense-ai1.8KFormulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Use when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.stock-research-executorliangdabiao1.8K股票投资调研执行引擎，执行8阶段投资尽调流程。接收stock-question-refiner生成的结构化调研指令，部署多智能体并行研究，生成带引用的投资尽调报告。覆盖：公司事实底座、行业周期、业务拆解、财务质量、股权治理、市场分歧、估值护城河、综合报告。当用户需要进行股票投资研究、基本面分析、投资尽调时使用此技能。database-lookupk-dense-ai1.8KQuery documented public database APIs with explicit endpoints, filters, pagination, and provenance. Use when a scientific, regulatory, financial, or other database-backed fact must be retrieved reproducibly from a named source rather than inferred from general knowledge.aksharesucc9851.8KChinese financial data access using AkShare library. Fetch real-time and historical data for A-shares, Hong Kong stocks, US stocks, futures, funds, and macroeconomic indicators. Use when user requests Chinese market data, stock prices, market analysis, or financial information from Chinese exchanges. Supports stock quotes, historical data, futures market data, fund information, macroeconomic indicators, and real-time market updates.nv-generate-mr-brain-finetunenvidia1.8KUsed for finetuning NV-Generate-CTMR MR-Brain v1 for T1, T2, FLAIR, SWI, or MRA data from a NIfTI datalist. Not for clinical or production data approval.scholar-evaluationk-dense-ai1.8KProvide qualitative-first, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with optional local quality controls. Never use for ranking people or consequential decisions.nv-segment-ctnvidia1.8KUsed for running NV-Segment-CT VISTA3D on CT NIfTI volumes and recording label-map evidence.requesthuntresciencelab1.8KGenerate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, GitHub, YouTube, LinkedIn, and Amazon. Use when user wants to do demand research, find feature requests, analyze user demand, or run RequestHunt queries.nv-segment-ct-finetunenvidia1.8KRuns standard or fixed-channel softmax finetuning of NV-Segment-CT VISTA3D on CT NIfTI image/label datasets, with optional MONAI-native MLflow tracking and checkpoint evidence. Uses softmax for predefined, mutually exclusive classes; keeps the standard workflow when point prompts or runtime-variable classes are needed. Not for clinical validation.bgpt-paper-searchk-dense-ai1.8KSearch scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.polarsk-dense-ai1.8KHigh-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.affinity-diagramowl-listener1.8KCluster many qualitative data points into themes and insight statements. Use when synthesising across multiple sessions or sources. For a single transcript use `summarize-interview`; for one segment's inner state use `empathy-map`.diary-study-planowl-listener1.8KDesign a diary study — prompts, cadence, duration, participant criteria, and analysis frame. Use when behaviour unfolds over days or weeks. For a single-session study, use `usability-test-plan`.deep-researchlingzhi2271.7KConduct systematic academic literature reviews in 6 phases, producing structured notes, a curated paper database, and a synthesized final report. Output is organized by phase for clarity.find-anyoneuseosint1.7KBuild a sourced, corroborated profile of a named individual from public records, social platforms, professional networks, court and property filings, licensing boards, patents, papers and obituaries — anchoring the name to a second selector first so you never fuse two people into one dossier. Use when asked to find, identify, background-check or profile a person, verify someone's claimed employment or credentials, or locate a missing or hard-to-reach individual. Applies to counterparty and invesnetworkxk-dense-ai1.7KCreate, analyze, and visualize complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.aeonk-dense-ai1.7KThis skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.sympyk-dense-ai1.7KUse when you need exact symbolic math in Python — algebra, calculus, equation solving, symbolic linear algebra, or code generation via lambdify/LaTeX. Prefer NumPy or SciPy when floating-point approximations are sufficient.pyzoterok-dense-ai1.7KInteract 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.compare-modelsreplicate1.7KCompare Replicate models by cost, speed, quality, and capabilities.shapk-dense-ai1.7KExplain and audit machine-learning predictions with SHAP. Use for selecting SHAP explainers and maskers, computing and validating feature attributions, handling multi-output explanations, and producing local or global SHAP visualizations.market-research-reportsk-dense-ai1.7KBuild evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.write-the-intel-briefuseosint1.7KTurn findings into a defensible intelligence product — BLUF key judgements, standardised estimative probability language, per-claim sourcing with timestamps and archived copies, separated observation, inference and assessment, documented negative findings and gaps, chain of custody and hashing, and redaction of uninvolved parties. Use when writing an intelligence report, due-diligence memo, evidence pack or executive summary, or when asked to write up an investigation so it survives challenge. Adaskk-dense-ai1.7KDistributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.matlabk-dense-ai1.7KBuild, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.geolocate-from-pixelsuseosint1.7KGeolocate and chronolocate a photo or video from visual evidence alone — plate and phone number formats, road markings, utility poles, bollards, signage typefaces, architecture and vegetation for place; shadow direction and length with SunCalc for time and date. Use when asked where or when a picture was taken, to verify a claimed location without GPS or EXIF, or to match a scene against Google Earth, Street View, Yandex Panoramas, Mapillary or KartaView. Applies to GEOINT and conflict monitoringraph-the-networkuseosint1.7KBuild an entity-relationship link-analysis graph of an investigation — nodes, typed edges carrying source and confidence, aliases, and temporal validity — to expose shared infrastructure, bridging nodes and the real principal behind a frontman. Covers Maltego, Neo4j and Cypher, Gephi, centrality and community detection, and entity resolution. Use when an investigation has outgrown a list and needs a graph, or when asked how a set of people, companies and domains connect. Applies to fraud-ring anscikit-survivalk-dense-ai1.7KBuild, evaluate, and audit right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.open-notebookk-dense-ai1.7KSelf-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+parallel-webk-dense-ai1.7KUse Parallel CLI for web search, URL extraction, deep research, structured data enrichment, entity discovery, and recurring web monitoring. Best for requests that explicitly need current web evidence, academic-source discovery, repeated entity lookups, exhaustive reports, or ongoing change tracking.pymck-dense-ai1.7KBayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.umap-learnk-dense-ai1.7KUse UMAP-learn for nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows.