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概要と使いどころ
Parse Flow Cytometry Standard (FCS) files v2.0–3.1 and extract events/metadata for preprocessing workflows (e.g., when you need NumPy arrays, channel info, or CSV/DataFrame export from cytometry files).
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Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.
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Use when you need a standardized R CLI workflow to build a protein-protein interaction network from a local gene list and an offline STRING cache, export node and edge tables, and render a reproducible PDF network plot. NOT for online API fetching, arbitrary graph databases, multi-omics integration, or non-STRING interaction sources.
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。
Use when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with a ROC PDF. NOT for: survival analysis, time-to-event outcomes, multiclass classification, calibration curves, decision-curve analysis, or nomogram construction.
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。
Use when constructing a prognosis nomogram from survival-related clinical predictors, exporting the nomogram bundle and C-index table, and optionally rendering the final nomogram PDF. NOT for: univariate/multivariable Cox feature screening, calibration curves, ROC analysis, decision-curve analysis, or non-survival outcomes.
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。
Use when performing correlation analysis between two variables including Pearson and Spearman correlation methods. Supports command-line parameter input, automatic data format detection, parameter validation, result directory creation, and CSV or TXT format result export.
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。
Use when performing PCA principal component dimensionality reduction on tabular numeric data. Supports command-line parameter input, automatic numeric feature selection, parameter validation, result directory creation, and CSV or TXT format result export.
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。
Use when running prognostic survival analysis on a clinical cohort with time-to-event data to estimate univariate and multivariable Cox proportional hazards models, export result tables, and generate forest plots. NOT for: nomogram construction, calibration curves, time-dependent ROC analysis, or model training/feature selection beyond the built-in univariate screening rule.
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。
Use when building a weighted gene co-expression network from a bulk expression matrix and a sample group file, filtering variable genes by MAD, identifying co-expression modules with WGCNA, correlating modules with traits, and exporting module-level plots and gene tables. NOT for single-cell RNA-seq, differential expression testing, methylation analysis, or datasets that are too small for WGCNA after quality control.
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。
Scrum-inspired paper review, revision, and R&R workflow. Handles docx/tex/md/PDF in English or Chinese. Auto-detects manuscript stage, estimates sprint count, runs multi-lens review (Contribution/Rigor/Writing/Editor), generates prioritized revision backlog, exports MD/DOCX/PDF/HTML reports. Use when asked to review a paper, revise based on reviewer comments, handle R&R, respond to peer review, plan paper revision sprints, or when user types /ps or /papersprint.
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。
Use when generating Kaplan-Meier survival curves from tabular survival data containing time, event status, and a precomputed risk group. Supports command-line parameter input, parameter validation, automatic time-unit handling, single-file PDF figure export, and session metadata capture.
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Run immune pathway GSVA or ssGSEA analysis from a bulk expression matrix, a sample group file, and a local immune Reactome gene-set table, then export differential pathway results and a heatmap for two-group comparison.
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。
Use when building a ceRNA regulatory network from a key gene list by combining bundled miRNA-mRNA and miRNA-lncRNA database files, with flat-file CSV exports and PDF visualization in a single output directory. NOT for: differential expression, single-cell analysis, enrichment analysis, or workflows without a key gene list.
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。
Use when building a decision tree model in R and generating feature importance ranking outputs. Supports classification and regression, automatic task detection, parameter validation, model evaluation summaries, and exports of feature-importance tables and figures.
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。
Use when evaluating the clinical utility of a binary prediction model from a single clinical CSV file by fitting a logistic decision-curve model, plotting decision and clinical-impact curves, and exporting summary outputs. NOT for: survival calibration, ROC-only discrimination analysis, nomogram construction, or time-to-event outcomes.
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。
Create logos using AI image generation. Discuss style/ratio, generate variations, iterate with user feedback, crop, remove background, and export as SVG. Use when user wants to create a logo, icon, favicon, brand mark, mascot, emblem, or design a logo.
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。
Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.
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Use whenever you generate or review a chart, plot, table, or paper figure in this workspace, including work delegated by paper-writing, literature-survey, and experiment skills. Applies the Open Science publication style, enforces readable final-size layout for figures and tables, and rejects generic diagram-tool output as a publication figure. Interactive Plotly/HTML may be used for exploration, but paper delivery requires a static publication-ready export.
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Set up or run the token build pipeline — transform the DTCG tokens/*.json (source of truth) into platform artifacts (CSS variables, Tailwind @theme, JS/TS, iOS Asset Catalog, Android, Compose) with Style Dictionary / Tokens Studio / W3C DTCG export. Use when the user wants to generate platform theme files from tokens, wire token CI, or multi-platform token output.
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Pre-screen analysis outputs (tables, figures, logs) built on restricted or confidential data for statistical-disclosure-limitation problems before any release. Scans for small cell counts, complementary-suppression gaps, dominance (p-percent / (n,k)), re-identifiable exact counts, PII leakage, and unrounded sensitive statistics; classifies each finding CRITICAL / WARNING / OK and gates on any CRITICAL. Use before depositing or sharing restricted-data results, or when the user says "disclosure check", "SDL scan", "is this output safe to release", "check for small cells", "disclosure avoidance", "pre-screen for the RDC", or "can I export this from the enclave".
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。
End-to-end Stata replication pipeline — scaffolds numbered `.do` files in `scripts/stata/`, executes them via the `stata-mcp` MCP server, captures logs and outputs to `output/`, and produces publication-ready tables (esttab) and figures (graph export). Mirrors `/data-analysis` for R-first projects. Use when user says "stata replication", "set up Stata pipeline", "scaffold the .do files", "run Stata analysis", "AEA replication package in Stata", or when a project's analysis language is Stata not R.
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。
Generate production subtitle artifacts from the final narration audio or final merged video using Volcengine Doubao ASR word timestamps. Use for local IndexTTS2 videos, Xiaohei page videos, talking-head delivery subtitles, SRT/VTT export, or whenever subtitle timing must match the final audio. Do not use script-length interpolation for final deliverables.
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Create dark cinematic SaaS/product motion videos in the Presenton-like "magic UI" style: black starfield stage, bottom purple glow, large kinetic type, cyan-to-magenta CTA buttons, prompt cards, floating UI templates, integration badges, model rings, export objects, speed-blur transitions, and short product capability arcs. Use when the user asks for "这种风格", "同款风格", dark SaaS promo, AI product demo, magic UI product video, or a style-level creation inspired by a reference video. Do not use for pixel-level or frame-accurate replication; use rn-replica-qc first for that.
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。
Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match), shortest paths, connected components, and graph-to-table export. Generates the edges-first thinking: define edges, define node lookups, union, make-graph. WHEN: make-graph, graph-match, graph-shortest-paths, graph-to-table, graph-mark-components, persistent graph, graph model, graph snapshot, build a graph from data, find paths between nodes, pattern matching in graph, connected components, transient graph, Kusto graph, KQL graph.
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。