「pipe flow」の検索結果

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

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 R data analysis pipeline — exploration → cleaning → regression → publication-ready tables and figures. Use when user says "analyze this dataset", "run a regression on X", "explore this CSV", "full analysis workflow", "get me summary stats and a regression", or points at a `.csv`/`.rds`/`.dta` and asks for empirical results. Produces numbered R scripts in `scripts/R/` and outputs to `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。

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。

Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.

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 troubleshoot Cloudflare Basin analytics workflows with Basin Pipelines, Basin Catalog, and Basin SQL. Use for streaming data into R2 Iceberg tables, managing catalogs, or querying those tables; also use for requests using the former Data Platform, Pipelines, R2 Data Catalog, or R2 SQL names.

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。

Set up Azure Pipelines for CI/CD, configure build and release pipelines, manage Azure DevOps projects, and integrate with Azure services. Use when working with Azure DevOps Services or Server for enterprise DevOps 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。

Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload pipelines.

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 nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.

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。

CI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment 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。

GitHub Actions workflow patterns, matrix builds, caching strategies, deployment pipelines, artifact management, and rollback procedures.

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。

Route an unbound research Goal to one Workflow or materialize its initial C0 kickoff block; use during initial binding, not for later checkpoint summaries or approval.

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 research Workflow end to end when the user requests a survey, brief, review, tutorial, or idea exploration; route an unbound goal, execute one eligible Unit at a time, and stop at checkpoints or diagnosed failures.

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。

Project completed stage Artifacts into a concise human-review block in `DECISIONS.md`; use before a Workflow checkpoint, not for Workflow routing or approval.

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。

Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).

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 ManagedCode.MarkItDown when a .NET application needs deterministic document-to-Markdown conversion for ingestion, indexing, summarization, or content-processing workflows. USE FOR: ManagedCode.MarkItDown integration; document ingestion flows; Office or rich-text conversion to Markdown; indexing and summarization pipelines. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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。

Entry point + orchestrator for the recomby-geo GEO (Generative Engine Optimization) workflow on OpenAI Codex CLI. Use when the user wants to run any stage of the GEO pipeline on a client folder — intake, visibility audit, content-gap analysis, content brief, draft production, distribution, or monthly re-audit — or asks to "run GEO", "audit AI search visibility", or "GEO this client". Codex has no bare slash commands, so this skill is how the 7 stages (that Claude Code runs as /01-intake … /07-reaudit) are driven on Codex. It routes to the per-stage specs in this plugin's commands/ and enforces the orchestration rules. Does not auto-fill expert content — the human-in-loop brief checkpoint is the moat.

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 you need to apply functional exception handling best practices in Java — including replacing exception overuse with Optional and VAVR Either types, designing error type hierarchies using sealed classes and enums, implementing monadic error composition pipelines, establishing functional control flow patterns, and reserving exceptions only for truly exceptional system-level failures. This should trigger for requests such as Improve the code with Functional Exception Handling; Apply Functional Exception Handling; Refactor the code with Functional Exception Handling; Model Java errors with Result or Either types; Replace exception-heavy flows with functional error handling. Part of Plinth Toolkit

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。

Trigger for: finding federal opportunities; capture and bid screening; competitor or incumbent intelligence; recompete pipelines; teaming partner research; agency, customer, or market intelligence; federal labor-rate or pricing context; or refreshing prior GovCon research. Always begin with the complete workflow menu and obtain the user's selection before research, preflight, file generation, web search, or MCP calls. Produce sourced chat findings or an optional validated GovCon Growth Brief without making a bid decision from public data alone.

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。

Python data pipelines with modular architecture. Use for content workflows, batch jobs, or Google Sheets/Drive integration.

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 GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.

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 multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

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。

Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.

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 multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

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 automated ETL (Extract-Transform-Load) pipelines for construction data. Process PDFs, Excel, BIM exports. Generate reports, dashboards, and integrate with other systems. Orchestrate with Airflow or n8n.

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。