Upload images to Imgur for free hosting. Use this skill when you need to upload images and get public URLs for sharing or embedding in articles.
Skills(SKILL.md)は、AIエージェント(Claude Code、Cursor、Codexなど)に特定の能力を追加するための設定ファイルです。
詳しく見る →Upload images to Imgur for free hosting. Use this skill when you need to upload images and get public URLs for sharing or embedding in articles.
Master skill for generating immunopipe pipeline configurations. Determines pipeline architecture based on data type (scRNA-seq with or without scTCR/BCR-seq) and analysis requirements. Routes to individual process skills for detailed configuration. Use this skill when starting a new immunopipe configuration or modifying pipeline-level options.
**IMPACT ANALYZER v1.0** - '영향도', '영향 범위', '변경 영향', '리팩토링 영향', '이거 바꾸면', '어디에 영향', '위험도' 요청 시 자동 발동. codebase-graph 기반 변경 전파 분석. 직접/간접 영향, 위험도 점수, 테스트 범위 제안. 코드 수정 전 필수 분석.
Step-by-step guide for implementing choreography patterns with event bus, idempotent consumers, correlation ID propagation, and query views.
Create D3 questions with unique, non-standard interactions. Fallback skill for questions not fitting standard patterns.
Create D3 questions with double number lines showing proportional relationships. Students complete missing values on parallel number lines.
Create D3 questions with drag-and-drop matching interactions. Students drag items (tables, graphs, equations) to categories.
Create interactive dilation animations using p5.js where students explore dilations with adjustable scale factors.
Create interactive coordinate plane questions using p5.js where students draw linear lines with snap-to-grid.
Create interactive tape diagram builders using p5.js where students construct algebraic equations by dragging and resizing parts.
Create D3 questions with +/- button controls and emoji/visual displays. Common for ratio, mixture, and recipe problems where students adjust quantities.
Create D3 questions with radio button selections and optional explanations. Students select from options and explain their reasoning.
Create D3 questions with interactive sliders and live visualization updates. Students adjust continuous values and observe dynamic feedback.
Implement code using sonnet model with full main context access
Create D3 questions with static line graphs and coordinating table inputs. Students read graphs and fill in corresponding values.
Create D3 questions with fill-in-the-blank tables. Students complete missing values based on patterns, rates, or relationships.
Create D3 questions focused on written explanations and reflections of static content (text, images, diagrams). For video-based questions, use implement-video-question instead.
Create D3 questions where students watch a video and provide written responses. The video is the primary instructional content.
Implements WPF 2D graphics using Shape, Geometry, Brush, and Pen classes. Use when building vector graphic UIs, icons, charts, or diagrams in WPF applications.
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
Set up RAG pipelines with document chunking, embedding generation, and retrieval strategies using LlamaIndex. Use when building new RAG systems, choosing chunking approaches, selecting embedding models, or implementing vector/hybrid retrieval for src/ or src-iLand/ pipelines.
Real-time communication patterns for live updates, collaboration, and presence. Use when building chat applications, collaborative tools, live dashboards, or streaming interfaces (LLM responses, metrics). Covers SSE (server-sent events for one-way streams), WebSocket (bidirectional communication), WebRTC (peer-to-peer video/audio), CRDTs (Yjs, Automerge for conflict-free collaboration), presence patterns, offline sync, and scaling strategies. Supports Python, Rust, Go, and TypeScript.
Import existing markdown files into Kurt database. Fix ERROR records, bulk import files, link content to database.
Download skill content from Notion and create it locally in `03-skills/`.
Quality control of phasing and imputation results. Filter by INFO scores, assess accuracy, and prepare imputed data for downstream analysis. Use when filtering low-quality imputed variants or validating imputation accuracy before GWAS.
Manage Gmail inbox with AI-powered triage, cleanup, and restore. Use when the user mentions inbox, email triage, clean inbox, email cleanup, check email, email summary, delete emails, manage inbox, or wants to organize their email.
Workflow for processing large Things3 inboxes (100+ items) using LLM-driven confidence matching and intelligent automation. Integrates with personal taxonomy and MCP tools for efficient cleanup with self-improving pattern learning.
インシデント調査で根本原因を特定するためのなぜなぜ分析ファシリテーションツールです。推測を避け、ユーザーの発言を記録し、リアルタイムでマインドツリーを作成して全体を可視化します。複合要因を分割し、最低1つの根本原因を特定します。
incident-handling
Build resilient data ingestion pipelines from APIs. Use when creating scripts that fetch paginated data from external APIs (Twitter, exchanges, any REST API) and need to track progress, avoid duplicates, handle rate limits, and support both incremental updates and historical backfills. Triggers: 'ingest data from API', 'pull tweets', 'fetch historical data', 'sync from X', 'build a data pipeline', 'fetch without re-downloading', 'resume the download', 'backfill older data'. NOT for: simple one-shot API calls, websocket/streaming connections, file downloads, or APIs without pagination.
Use when working with inductor components - adding inductor patterns, parsing inductor MPNs, extracting inductance values, current ratings, or package codes from inductor part numbers.
Terraform/Docker Composeによるインフラ構築のワークフロー、ベストプラクティス、Well-Architected Framework対応を定義
Infrastructure, DevOps, and platform reliability
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Data ingestion patterns for loading data from cloud storage, APIs, files, and streaming sources into databases. Use when importing CSV/JSON/Parquet files, pulling from S3/GCS buckets, consuming API feeds, or building ETL pipelines.
Unified atomic ingestion of CFN dependency manifests (trigger-dev, cli-mode, shared)
Create or update CLAUDE.md file for this project. Use when initializing a project for Claude Code, or when project structure/architecture has significantly changed.
Use when starting a new session without feature-list.json, setting up project structure, or breaking down requirements into atomic features. Load in INIT state. Detects project type (Python/Node/Django/FastAPI), creates feature-list.json with priorities, initializes .claude/progress/ tracking.
Achieve and maintain low input latency by engineering event-to-render pipelines.
Design, standardize, and implement ECharts-based visualizations and themes for InsightPulseAI dashboards, Superset plugins, and OpEx UI (AntD + M3 + ECharts).
Use Superset-style APIs to manage workspaces, users, datasets, charts, and dashboards as code for the InsightPulseAI Data Lab platform.
Design and configure embedded Superset dashboards for internal tools and customer apps with theming, RLS, SSO, and scalable UX.
Instagram Graph API entegrasyonu. Use when publishing content, fetching insights, or working with Instagram media.
You are an expert in the Instagram US Reels search pipeline for this influencer discovery platform. This skill provides comprehensive knowledge about search providers, rate limits, normalization logic
Instagram Graph API integration via curl. Use this skill to fetch and publish Instagram media.
This skill installs an interactive learning graph viewer application into an intelligent textbook project. Use this skill when working with a textbook that has a learning-graph.json file and needs a visual, interactive graph exploration tool with search, filtering, and statistics capabilities.
MCP サーバーをインストールする。「MCP インストール」「MCP を追加」「MCP サーバー追加」「mcp add」「MCP を入れて」「MCP サーバーをインストール」「新しい MCP」などで起動。
Instantly.ai cold email outreach API - manage campaigns, leads, accounts, and analytics. Use for cold email automation, lead management, campaign creation/monitoring, and email account warmup.
Structured outputs with Instructor. Extract typed data from LLMs using Pydantic models and validation. Use for data extraction, structured generation, and type-safe LLM responses.
Use when defining events, fields, and governance for GTM analytics pipelines.