Bayesian parameter estimation with MCMC (emcee) and probabilistic programming (PyMC). Posterior distributions, corner plots, model evidence, convergence diagnostics. Use when you need full posterior distributions, not just point estimates.
日本語の概要は準備中です。原文の説明を表示しています。
huang-sh/DeepScience☆ 42026年7月15日 更新
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
日本語の概要は準備中です。原文の説明を表示しています。
huang-sh/DeepScience☆ 42026年7月15日 更新
Build AI scientist systems with the ToolUniverse Python SDK for scientific research. Covers the 3 calling patterns (`tu.run` portable dict API, `tu.tools.X` function API, direct class instantiation), tool loading, batch execution, MCP server integration, and embedding-based tool search. Use for SDK programming, custom tool composition, benchmarking pipelines, and integrating ToolUniverse into research workflows.
日本語の概要は準備中です。原文の説明を表示しています。
huang-sh/DeepScience☆ 42026年7月15日 更新
Runs the MS-DIAL preprocessing workflow (peak picking, MS2Dec spectral deconvolution, alignment, gap-filling) and imports the alignment-result table into R or Python with honest filtering. Use when preprocessing LC-MS DDA/DIA (SWATH) raw data with MS-DIAL, deciding MS-DIAL vs XCMS, configuring the MsdialConsoleApp console run, or parsing an MS-DIAL export into a clean feature matrix. For programmatic R peak detection and the feature-table-as-artifact framing see metabolomics/xcms-preprocessing; for lipid annotation mode see metabolomics/lipidomics; for MSI-level confidence honesty see metabolomics/metabolite-annotation; for drift correction and QC see metabolomics/normalization-qc.
日本語の概要は準備中です。原文の説明を表示しています。
huang-sh/DeepScience☆ 42026年7月15日 更新
Programmatic untargeted LC-MS feature extraction in R with the modern xcms 4.x MsExperiment/XcmsExperiment API, taking raw mzML to a feature table via CentWave peak detection, retention-time alignment, peak-density correspondence, gap-filling, CAMERA redundancy collapse, and built-in QC feature filtering. Use when converting centroided LC-MS runs into a features-by-samples matrix and deciding centWave/grouping/alignment parameters. For drift correction and QC/CV filtering execution see metabolomics/normalization-qc; for metabolite identification see metabolomics/metabolite-annotation; for the MS-DIAL GUI alternative with MS2Dec deconvolution see metabolomics/msdial-preprocessing; for downstream statistics see metabolomics/statistical-analysis.
日本語の概要は準備中です。原文の説明を表示しています。
huang-sh/DeepScience☆ 42026年7月15日 更新
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.
日本語の概要は準備中です。原文の説明を表示しています。
gracefullight/pkgs☆ 42026年10月2日 更新
Plan AI pilot programs with success criteria. TRIGGERS - Use when user needs help with ai-pilot-plan related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Winbda/claude-skills-collection☆ 42026年4月6日 更新
Design white-label programs. TRIGGERS - Use when user needs help with agency-white-label-plan related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Winbda/claude-skills-collection☆ 42026年4月6日 更新
Plan affordable housing programs. TRIGGERS - Use when user needs help with affordable-housing-plan related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Winbda/claude-skills-collection☆ 42026年4月6日 更新
Optimize affiliate programs with commission and activation. TRIGGERS - Use when user needs help with affiliate-optimization related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Winbda/claude-skills-collection☆ 42026年4月6日 更新
Design 360-degree feedback programs with surveys. TRIGGERS - Use when user needs help with 360-feedback related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Winbda/claude-skills-collection☆ 42026年4月6日 更新
Use when building or reviewing core Quarkus applications with CDI beans and scopes, SmallRye Config and profiles, lifecycle, interceptors and events, virtual threads, and test-friendly design. This should trigger for requests such as Review Java code for Quarkus application structure and CDI; Apply best practices for Quarkus configuration and beans; Improve CDI interceptors, events, or programmatic injection in Quarkus; Add virtual-thread configuration or tune CDI lifecycle. Part of cursor-rules-java project
日本語の概要は準備中です。原文の説明を表示しています。
aibot88/sec_skill_store☆ 42026年5月27日 更新
Use when you need to write or review programmatic JDBC with Spring — including JdbcClient (Spring Framework 7+) as the default API, JdbcTemplate only where batch/streaming APIs require JdbcOperations, NamedParameterJdbcTemplate for legacy named-param code, parameterized SQL, RowMapper mapping to records, batch operations, transactions, safe handling of generated keys, DataAccessException handling, read-only transactions, streaming large result sets, and @JdbcTest slice testing. This should trigger for requests such as Review Java code for Spring JDBC (JdbcTemplate, JdbcClient, NamedParameterJdbcTemplate); Apply best practices for Spring JDBC data access in Java code; Detect and fix SQL injection risks in JDBC code; Improve transaction boundaries or exception handling for JDBC operations. Part of cursor-rules-java project
日本語の概要は準備中です。原文の説明を表示しています。
aibot88/sec_skill_store☆ 42026年5月27日 更新
Configures 1Password CLI with direnv for fast, secure credential loading. Activates for: 1Password + direnv setup, slow secrets (>2 sec), .env.op files, op:// references, AWS credentials via env vars, --reveal flag issues, repeated biometric prompts, creating 1Password items programmatically, op item get errors. Not for: 1Password GUI usage, SSH keys (use 1Password SSH agent).
日本語の概要は準備中です。原文の説明を表示しています。
aibot88/sec_skill_store☆ 42026年5月27日 更新
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/TRACE☆ 32026年10月11日 更新
Run remote BLAST searches against NCBI servers using Biopython Bio.Blast.NCBIWWW. Use when identifying unknown sequences, finding homologs, picking the correct BLAST program (blastn/blastp/blastx/tblastn/tblastx/psiblast/megablast/dc-megablast), interpreting Karlin-Altschul E-values, avoiding the max_target_seqs trap (Shah 2019), choosing composition-based statistics, or limiting searches by organism. Covers RID lifecycle, database choice (nt/nr/refseq_select/swissprot), word-size and CBS taxonomy.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/TRACE☆ 32026年10月11日 更新
Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/TRACE☆ 32026年10月11日 更新
Build static sites with Nitro CLI - a Python static site generator using nitro-ui for programmatic HTML generation instead of templates
日本語の概要は準備中です。原文の説明を表示しています。
nitrosh/nitro-cli☆ 32026年10月11日 更新
Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.
日本語の概要は準備中です。原文の説明を表示しています。
phoroth/AGENTIC☆ 32026年8月8日 更新
Comprehensive patterns and techniques for analyzing compiled binaries, understanding assembly code, and reconstructing program logic.
日本語の概要は準備中です。原文の説明を表示しています。
phoroth/AGENTIC☆ 32026年8月8日 更新
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models.
日本語の概要は準備中です。原文の説明を表示しています。
phoroth/AGENTIC☆ 32026年8月8日 更新
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
日本語の概要は準備中です。原文の説明を表示しています。
phoroth/AGENTIC☆ 32026年8月8日 更新
Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
日本語の概要は準備中です。原文の説明を表示しています。
phoroth/AGENTIC☆ 32026年8月8日 更新
Process, parse, create, and manipulate Microsoft Word (.docx) documents programmatically using libraries like docx or mammoth.js for document generation and data extraction. Use when generating Word documents from templates, extracting text and formatting from .docx files, creating reports and invoices, parsing resumes and forms, converting Word to HTML, creating mail merge documents, or automating document workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Fabric-Pro/fabric-oss☆ 32026年10月9日 更新