「data flow」の検索結果

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

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。

Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow 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。

How to read submitted JetFormBuilder form data from a custom action, transform it (including %macro% replacement of admin-typed templates), call an external HTTP API, write the response back into the form context for downstream actions to use, and dispatch JFB events based on the API outcome. Use when building a custom action that integrates with a third-party service (LLM call, webhook, CRM, payment processor, geolocation lookup) and needs the action to behave as a node in a data-flow graph rather than a one-shot leaf. Triggers on mentions of "jet_fb_context", "update_request", "has_field", "get_value", "wp_remote_post" with form data, "macro replacement", or "API call from action".

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。

Run a comprehensive health check on a single Estuary task by combining catalog status, data flow stats, recent errors, and publication history. Use when diagnosing a task that seems broken, slow, or stuck. Use when user says "is my task healthy", "something seems wrong", "check my capture", "check my materialization", "why is data not flowing", "task health check", "diagnose my task", or "what's wrong with my pipeline".

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 an Alpaca capture using flowctl to stream stock trade data into Estuary collections. Use when setting up an Alpaca Market Data source for historical and real-time stock trades. Use when user says "capture Alpaca", "stream stock trades", "Alpaca market data", or "connect Alpaca to Estuary".

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。

Builds native iOS apps in Swift — SwiftUI and UIKit screens, state and data flow, NavigationStack, lists, forms and accessibility; networking with URLSession and Codable, persistence with SwiftData, Core Data, files and the Keychain; permissions, push notifications, universal links, background tasks, widgets, App Intents and StoreKit 2 purchases; performance with Instruments and MetricKit; and release with signing, TestFlight and App Store Connect. Use when writing or changing native iOS code, adding a platform feature, preparing a build for TestFlight or the App Store, or when the user asks how to do something on iOS, even if they do not name the framework.

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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

Uses AWS Athena to query CloudTrail, VPC Flow Logs, S3 access logs, and ALB logs for forensic investigation. Covers CREATE TABLE DDL with partition projection, forensic SQL queries for Tespit etme unauthorized access, data exfiltration, lateral movement, and privilege escalation. Use investigating yaparken AWS security incidents or building cloud-native forensic workflows at scale.

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。

Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow 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。

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

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 Sankey, alluvial, river, and CONSORT-style flow diagrams to visualize cohort transitions, cell-state changes, or pipeline filtering using ggalluvial, networkD3, plotly, and consort. Use when showing how entities move between categories across timepoints (cell states, drug response classes, patient flow through a trial) or filtering pipelines (variants filtered through QC stages).

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 single-cell RNA-seq workflow from 10X Genomics data to annotated cell types. Covers QC, normalization, clustering, marker detection, and cell type annotation. Use when analyzing single-cell RNA-seq data.

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 multiome workflow for joint scRNA-seq + scATAC-seq analysis. Covers data loading, separate modality processing, and WNN integration with Seurat/Signac. Use when analyzing joint scRNA+scATAC data.

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 biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, leakage-safe cross-validation, calibration, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.

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 multi-omics integration workflow. Orchestrates data harmonization, MOFA/mixOmics integration, factor interpretation, and downstream analysis across transcriptomics, proteomics, metabolomics, and other modalities. Use when integrating multiple omics datasets.

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。

Design data annotation workflows for AI. TRIGGERS - Use when user needs help with ai-annotation-workflow 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。

Bootstrap a complete .github/workflows/ set for a new project: CI (build/test/lint), CD (workflow_dispatch with env choice + OIDC + ECR), security-scan (gitleaks + dependency scan + CodeQL), and optional database-migration. Use this skill when the user wants to add GitHub Actions CI/CD to a project that does not already have it, or when they want to add missing workflows alongside existing ones.

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。

Corrects fluorophore spillover (conventional compensation) or spectral overlap (spectral unmixing) and applies variance-stabilizing transforms (logicle/biexponential, arcsinh, log) for flow and mass cytometry. Covers spillover-matrix estimation from single-stain controls, AutoSpill, the spillover spreading matrix and why panel design (not compensation) bounds resolution, compensate-then-transform ordering, and arcsinh cofactor choice (5 for CyTOF, ~150 for fluorescence, per-channel via flowVS). Use when correcting spectral overlap, preparing data for gating/clustering, choosing logicle vs arcsinh, deciding a cofactor, or distinguishing compensation from spectral unmixing.

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 Sankey, alluvial, river, and CONSORT-style flow diagrams to visualize cohort transitions, cell-state changes, or pipeline filtering using ggalluvial, networkD3, plotly, and consort. Use when showing how entities move between categories across timepoints (cell states, drug response classes, patient flow through a trial) or filtering pipelines (variants filtered through QC stages).

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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

新しいスキルの雛形（ディレクトリ + SKILL.md）を本リポジトリの規約どおりに生成する。 frontmatter（name / description / 任意の argument-hint・disable-model-invocation・metadata.version）と 本文（# /SKILL_NAME スキル → Goal / Workflow / Notes）を対話的に埋め、 `.claude/rules/skill-authoring.md` の判断軸で置き場所（ai-agents/skills / ai-agents/personal/skills / .claude/skills）を選んで配置する。 新しいスキルを新規作成・立ち上げたいときに `/skill-scaffold <スキル名> [用途の一言]` で呼び出す。