「pipeline」の検索結果

Designs event-driven architectures, webhook systems, API chaining flows, ETL pipelines, and integration patterns between services.

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。

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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。

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD 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。

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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 planning a modeling solution, selecting the next useful step or briefing a specialist.

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。

Automated cookie consent validation using Selenium and Playwright. Covers banner interaction testing, consent state verification, tag firing audit after consent choices, regression testing for cookie compliance, and CI/CD pipeline 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。

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

Modern Python project architecture guide for 2025. Use when creating Python projects (APIs, CLI, data pipelines). Covers uv, Ruff, Pydantic, FastAPI, and async patterns.

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。

DevOps and CI/CD expert. Use when setting up pipelines, containerizing applications, deploying to Kubernetes, or implementing release strategies. Covers GitHub Actions, Docker, K8s, Terraform, and GitOps.

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。

Fill a raw PowerPoint (.pptx) template with new content by cloning and patching native slides — no SVG conversion, original design preserved, verified through a mandatory OfficeCLI overflow/render loop. Use whenever the user supplies an existing .pptx template or deck plus new material or a topic and wants a generated PPTX, even if they don't say "template" — "use this PPT template to generate a PPTX", "fill this deck with the new content", "replace the copy in this PowerPoint", "keep the original design and swap in this material", "이 템플릿에 내용 채워줘", "이 PPT 양식으로 만들어줘", "기존 PPT 디자인 그대로 내용만 교체해줘". Do NOT use for reusable template package creation (ppt-master create-template), 1:1 beautify, SVG-pipeline deck generation, or finished-PPTX enhancement (native-enhance-pptx).

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。

Post-router owner for authoring or regenerating presentation visuals through the PPT Master SVG pipeline: new decks from source material or a topic, PPTX re-architecture, generation from an already-created reusable SVG-template workspace, and shared SVG steps only after a strict 1:1 beautify workflow explicitly hands off. Read workflows/routing.md first. Do not use for ambiguous existing-PPTX optimization, reusable-template creation, raw-PPTX native filling, or finished-PPTX native enhancement; those are pre-route or standalone workflow requests.

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Multi-channel demand generation, paid media optimization, SEO strategy, and partnership programs for Series A+ startups. Includes CAC calculator, channel playbooks, HubSpot integration, and international expansion tactics. Use when planning demand generation campaigns, optimizing paid media, building SEO strategies, establishing partnerships, or when user mentions demand gen, paid ads, LinkedIn ads, Google ads, CAC, acquisition, lead generation, or pipeline generation.

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Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.

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Use when asked to make a launch video, product film, motion design piece, UI motion reel, Dribbble-style UI animation or animated brand/logo sting — anything rendered to MP4 from HTML with a cursor, morphing UI, springs, beat-synced music and SFX. Carries Chan's full creative direction (one shape never cut, blur content swaps, springs, real data, logo slams, no creative limits) and the proven build/render pipeline (pure seek(t), closed-form springs, Playwright subframes, ffmpeg tmix, numpy beat grid).

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。

Assembla integration. Manage Organizations, Leads, Deals, Pipelines, Users, Goals and more. Use when the user wants to interact with Assembla 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。

ApiFlash integration. Manage Organizations, Pipelines, Projects, Users, Filters. Use when the user wants to interact with ApiFlash 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。

Apex 27 integration. Manage Organizations, Pipelines, Users, Goals, Filters. Use when the user wants to interact with Apex 27 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。

Apollo.io integration. Manage Persons, Organizations, Deals, Leads, Pipelines, Users and more. Use when the user wants to interact with Apollo.io 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。

Api4ai integration. Manage Leads, Persons, Organizations, Deals, Projects, Pipelines and more. Use when the user wants to interact with Api4ai 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。

Ambivo integration. Manage Organizations, Pipelines, Users, Filters, Activities, Notes and more. Use when the user wants to interact with Ambivo 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。

Affinity integration. Manage Organizations, Leads, Pipelines, Users, Roles, Filters. Use when the user wants to interact with Affinity 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。