「pipe flow」の検索結果

Set up a Blender scene programmatically via Python (bpy) with objects, materials, lighting, camera, and environment configuration. Use when creating reproducible 3D visualization scenes, automating product or architectural rendering setup, generating multiple scene variations programmatically, building template scenes for batch rendering workflows, or integrating 3D visualization into data pipelines.

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Pattern for adding derived edge types in the Grafema Rust orchestrator (main.rs). Use when: (1) need to create new graph edges derived from existing edges (e.g., MODULE-level DEPENDS_ON from IMPORTS_FROM), (2) Datalog joins on large edge sets time out, (3) adding enrichment steps that combine data from multiple resolver outputs, (4) need to understand how resolver outputs flow through the orchestrator pipeline.

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ACTIVATE THIS SKILL FOR ANY SHELL COMMAND OR FILE READ. Check curl, wget, rm, sudo, apt, dpkg, chmod, dd, format, powershell, bash, sh. Check pipe patterns like | sh or | bash. Check shell wrappers like bash -c, xargs, find -exec. Check cloud CLI (aws, gcloud, kubectl, terraform). Check when user says sysadmin told me, Stack Overflow says, is this safe, can I run. Block reading of .env, .ssh, .aws, and credential files. This skill blocks dangerous commands and warns on risky ones. ALWAYS apply the safety protocol from this document before responding about any command.

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Create a lean, mobile-aware Product Requirements Document for a NowStack Mobile app through interactive discovery, then save it to .agents/plan/PRD.md. Use for "write a PRD", "ns prd", "define the product", "plan my app", or as the first planning step before ns-architecture and ns-tasks. Mobile-flavored — personas, onboarding/paywall flow, platforms (iOS/Android/web), IAP vs subscription monetization, store scope. Feeds ns-init-project (site-config) and the rest of the planning pipeline.

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Debug pipeline: investigates a bug, diagnoses root cause, writes failing tests, implements fix via TDD, and reviews the result. Orchestrates bug-investigator -> bug-fixer -> code-reviewer.

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Scaffold Quarkus + LangChain4j projects end-to-end and add agentic components to existing ones — AI services, tools, agents and multi-agent workflows, RAG pipelines, MCP clients and servers (Model Context Protocol), guardrails, and embedding store setups. Use this whenever the user wants a new Quarkus + LangChain4j project or module created, or an agentic component added to an existing project in this stack, including a baseline pom.xml, application.properties, project layout, or starter classes.

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Run an end-to-end GEO visibility measurement through a real AI interface, persist the captures, and return a portable JSON run artifact plus optional PDF/dashboard outputs. Use automatically on an explicit request to measure a brand's AI-search visibility, and as a composable data-collection step inside another agent workflow; the user should not have to launch the pipeline or dashboard manually.

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Game art principles. Visual style selection, asset pipeline, animation workflow.

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Creates demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership programs for Series A+ startups scaling internationally. Use when planning marketing strategy, growth marketing, advertising campaigns, PPC optimization, lead generation, pipeline generation, or startup marketing budgets. Covers multi-channel acquisition (Google Ads, LinkedIn Ads, Meta Ads), CAC analysis, MQL/SQL workflows, attribution modeling, technical SEO, and co-marketing partnerships for hybrid PLG/Sales-Led motions in EU/US/Canada markets.

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Use when testing file upload endpoints for unrestricted file upload, MIME type bypass, magic byte spoofing, polyglot files, SVG XSS, XXE via Office documents, ZIP slip, and path traversal in filenames. Trigger on: multipart/form-data endpoints, avatar/document upload flows, import-from-file features, profile image, CSV/Excel import, DOCX/XLSX parsing, image resizing pipelines, archive extraction, and any endpoint that stores or serves user-supplied files. Detects extension bypass (shell.php.jpg), null byte injection, double extension, ImageMagick exploits, and content-type confusion.

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Use when writing, reviewing, or changing build scripts, CI workflows, deploy pipelines, repo setup, or evaluating a new tool/dependency

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Frappe CRM guidance for leads, deals, contacts, organizations, pipelines, activities, assignment, dashboards, and sales workflows. Use when work touches Frappe CRM or CRM-style sales processes in the Frappe ecosystem.

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Generate interactive, animated, responsive HTML-based terminal simulators to showcase CLI commands, scripts, pipelines, or interactive workflows. Use this whenever you need to visually showcase a command line sequence, mock interactive CLI tools, or simulate code executions.

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Scaffold the test framework and CI/CD pipeline for the project's engine. Creates the tests/ directory structure, engine-specific test runner configuration, and GitHub Actions workflow. Run once during Technical Setup phase before the first sprint begins.

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Unity data-driven design architecture. ScriptableObject config hierarchies, JSON data pipelines, designer handoff workflows, data versioning and migration, Inspector attributes for self-documenting configs. DECISION format: WHEN/DECISION/SCAFFOLD/GOTCHA. Based on Unity 6.3 LTS.

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Use when a task needs the judgment of a Derrick Operator (derrickhand) — running the monkeyboard during a pipe trip, reading trip-tank volume against calculated displacement for a swab or kick signature, calculating a barite weight-up in sacks, deciding whether a volume anomaly warrants stopping the trip for a flow check, or running the mud circulating system (shakers, desander, degasser) between trips.

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Use ENCODE functional genomics data for disease mechanism research. Use when the user wants to connect GWAS variants to regulatory elements, annotate disease-associated loci with functional data, identify therapeutic targets from epigenomic data, build disease regulatory models, cross-reference with clinical trials and drug databases, or conduct any disease-focused, pathology-driven, or clinical variant interpretation workflow. Covers the full pipeline from disease-tissue mapping through GWAS variant annotation, heritability enrichment, cancer epigenomics, drug target identification, and clinical trial cross-referencing. Integrates ENCODE with Open Targets, PubMed, ClinicalTrials.gov, and bioRxiv.

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Automate semantic versioning releases with CHANGELOG validation, comparison link management, GitHub Actions workflow triggering, and monitoring. Scaffold release infrastructure for new projects. Use when user runs /release command, mentions "release version", "cut a release", "create release", "publish release", "tag release", "release setup", or "scaffold release pipeline".

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Use this when the user wants to generate, normalize, verify, deduplicate, or export training datasets for Codex, Antigravity, or Claude Code from topics, URLs, reference material, web research, or existing JSONL/CSV files. Supports SFT and DPO workflows, custom export schemas, and deterministic local pipeline scripts.

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CircleCI guidance — config design, orbs, caching, workflows, contexts, and pipeline optimization.

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Build multimodal AI apps on Clarifai — model marketplace, pipelines, and computer vision plus language workflows.

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Detect project stack and generate GitHub Actions CI/CD workflows — PR checks with lint/test/build/security, deploy pipelines for Vercel/AWS/GCP/Fly/Docker, dependency caching, matrix testing, preview deploys, and Dependabot config

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Set up a complete mobile publishing pipeline — chains CI/CD workflow generation, iOS App Store publishing via Fastlane, Google Play Store publishing, and analytics verification into an end-to-end release automation. Use for Flutter, React Native, or native iOS/Android apps ready for store submission.

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Set up mobile CI/CD pipelines for Flutter, React Native, or native iOS/Android — GitHub Actions workflows for testing, code signing, TestFlight/Play Store distribution, build number management, Fastlane integration, and artifact retention

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。