数据与 AI技能

Category-theoretic pipes with GF(3) flow balance checking. Validates data transformation pipelines using triadic trit algebra.

中文简介正在准备中。当前显示原文说明。

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

中文简介正在准备中。当前显示原文说明。

Semantic embeddings for Clojure code navigation via CIDER

中文简介正在准备中。当前显示原文说明。

CatColab Schemas - database schema modeling distinguishing entities (tables) from attributes (columns). Foundation for ACSets (Attributed C-Sets) and AlgebraicJulia data structures.

中文简介正在准备中。当前显示原文说明。

Intercept and debug Claude Code API requests using mitmproxy. Inspect system prompts, tool definitions, token usage, and streaming responses. Triggers: cc-trace, mitmproxy, API interception, Claude Code debugging, traffic inspection.

中文简介正在准备中。当前显示原文说明。

Interleave layer bridging the BigQuery cluster to plurigrid/asi. Routes BigQuery queries through asi's DuckDB stack, wires patent search into asi knowledge graph, connects Looker Studio dashboards to CatColab, and feeds BigQuery ML into the lolita physics emulation pipeline.

中文简介正在准备中。当前显示原文说明。

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.

中文简介正在准备中。当前显示原文说明。

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

中文简介正在准备中。当前显示原文说明。

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

中文简介正在准备中。当前显示原文说明。

Layer 1 - Data Acquisition for Bluesky/AT Protocol social graph and content.

中文简介正在准备中。当前显示原文说明。

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

中文简介正在准备中。当前显示原文说明。

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

中文简介正在准备中。当前显示原文说明。

Category-theoretic graph rewriting with DPO, SPO, and SqPO pushouts for C-Sets. Declarative transformation of acset data structures.

中文简介正在准备中。当前显示原文说明。

When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," or "tracking plan." For A/B test measurement, see ab-test-setup.

中文简介正在准备中。当前显示原文说明。

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

中文简介正在准备中。当前显示原文说明。

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

中文简介正在准备中。当前显示原文说明。

Attributed C-Sets as algebraic databases. Category-theoretic data structures generalizing graphs and dataframes with Gay.jl color integration.

中文简介正在准备中。当前显示原文说明。

This 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.

中文简介正在准备中。当前显示原文说明。

Bria.ai image API — generate from text prompts, edit with natural language, remove backgrounds for transparent PNGs, and create product lifestyle shots. Authenticates via OAuth device flow, caches credentials in ~/.bria/credentials, calls 20+ endpoints. Commercially safe, royalty-free. Triggers on: remove background, transparent PNG, cutout, generate image, create banner, edit photo, product photography, upscale, restyle, inpainting, outpainting, lifestyle shot, background replacement, object removal, photo restoration.

中文简介正在准备中。当前显示原文说明。

Maximum control over AI image generation — write structured VGL (Visual Generation Language) JSON that explicitly controls every visual attribute. Define exact object placement, lighting direction, camera angle, lens focal length, composition, color scheme, and artistic style as deterministic JSON instead of ambiguous natural language. Use this skill when you need reproducible image generation, precise control over scene composition, or want to convert a natural language image request into a structured JSON schema for Bria Fibo models. Triggers on requests for structured prompts, controllable generation, VGL JSON, deterministic image descriptions, or Bria/FIBO structured_prompt format.

中文简介正在准备中。当前显示原文说明。

用户在周期性复盘 X 内容数据、分析哪些内容类型表现好、决定下步内容策略调整时使用。四步闭环:数据收集(拉曝光/互动/收藏)→原因分析(按内容类型对比,查Hook/Body/CTA)→优化迭代("如果重来怎么做更好")→记录追踪(Notion模板闭环)。找20%贡献80%价值的内容加倍投入。周复盘聚焦数据(互动率),月复盘审视战略(变现路径)。Trigger signals:"这周发了15条怎么复盘""哪些类型互动高""下周内容策略怎么调""帮我分析数据"/"weekly content review""which content type performs better""optimize next week's content"。不适用于:单条内容生产(用x-short-content-craft)、帖子没爆焦虑心态(用x-longtail-strategy)、理解推荐算法机制(用x-foryou-algorithm)。

中文简介正在准备中。当前显示原文说明。

Analyze the sentiment or mood conveyed by an image with a local vision LLM. Wraps kuzco's tool_llm_image_sentiment() ellmer tool. Use when the task needs the emotional tone of an image, e.g. for content moderation, marketing, or curation.

中文简介正在准备中。当前显示原文说明。

Recognize and locate instances of an object in an image with a local vision LLM. Wraps kuzco's tool_llm_image_recognition() ellmer tool. Use when the task needs finding, counting, or locating specific objects (faces, cars, animals) in an image.

中文简介正在准备中。当前显示原文说明。

Extract text visible in an image (OCR) with a local vision LLM. Wraps kuzco's tool_llm_image_extract_text() ellmer tool. Use when the task needs reading text from screenshots, documents, signs, labels, or any image containing writing.

中文简介正在准备中。当前显示原文说明。