「production」の検索結果

You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.

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Master Go 1.21+ with modern patterns, advanced concurrency, performance optimization, and production-ready microservices. Expert in the latest Go ecosystem including generics, workspaces, and cutting-edge frameworks. Use PROACTIVELY for Go development, architecture design, or performance optimization.

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You are an expert error analysis specialist with deep expertise in debugging distributed systems, analyzing production incidents, and implementing comprehensive observability solutions.

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Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.

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Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.

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Expert SRE incident responder specializing in rapid problem resolution, modern observability, and comprehensive incident management. Masters incident command, blameless post-mortems, error budget management, and system reliability patterns. Handles critical outages, communication strategies, and continuous improvement. Use IMMEDIATELY for production incidents or SRE practices.

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Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.

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Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles production outages, system reliability, and preventive monitoring. Use PROACTIVELY for debugging, incident response, or system troubleshooting.

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Implement DeFi protocols with production-ready templates for staking, AMMs, governance, and lending systems. Use when building decentralized finance applications or smart contract protocols.

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You are a debugging expert specializing in setting up comprehensive debugging environments, distributed tracing, and diagnostic tools. Configure debugging workflows, implement tracing solutions, and establish troubleshooting practices for development and production environments.

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Build production-ready Web3 applications, smart contracts, and decentralized systems. Implements DeFi protocols, NFT platforms, DAOs, and enterprise blockchain integrations. Use PROACTIVELY for smart contracts, Web3 apps, DeFi protocols, or blockchain infrastructure.

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Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.

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Master of defensive Bash scripting for production automation, CI/CD pipelines, and system utilities. Expert in safe, portable, and testable shell scripts.

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Elite code review expert specializing in modern AI-powered code analysis, security vulnerabilities, performance optimization, and production reliability. Masters static analysis tools, security scanning, and configuration review with 2024/2025 best practices. Use PROACTIVELY for code quality assurance.

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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.

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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

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Smallest personal narrated-explainer-video pipeline (spoken narration over visuals, not an audio podcast), fully tool-agnostic and autonomous by default — topic → research ∥ asset collection → script → TTS → video → 4K render ∥ publish info + cover. The skill defines the pipeline logic and self-verified checkpoints; any TTS backend and any video tool (Remotion, HyperFrames, CapCut, ...) work, and how much human oversight to apply is set by the working project's AGENTS.md/CLAUDE.md, not here. Use when the user wants a quick personal narrated video with minimal steps, whether or not they name the tool stack. Do NOT trigger for audio-only podcasts, written episodic content, or heavy multi-format production.

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Minimal personal narrated-video pipeline — a topic becomes a talking-head-free explainer MP4 (1080p or 4K) via script → Azure TTS (SSML) → Remotion. Use when the user wants a quick narrated video from a topic without the full video-podcast-maker machinery (no extra skills, no thumbnails/shorts/publish matrix). Do NOT trigger for heavy production needs — use video-podcast-maker for those.

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Mainland-Chinese TV-series craft, documents and production chain (国产剧创作体系与制片链) — the China layer parallel to the Japanese and Korean/French skills. Distilled from Yao Kougen 姚扣根《电视剧写作概论》(2016; series taxonomy, four Chinese script formats, the 3-minute/15-minute/episode-end suspense law, 36 situations), Zhang Wei 张巍《电视剧改编教程》(2014; five source types, sell-point migration, six case studies), Zhang Mingzhi & Song Peiyi《电视剧出品人与制片人教程》(2016; running-time rules, two-stage censorship, scene-breakdown sheet, contracts), Zhao Binbin《影视剧片段改编教程》(2016; film to stage fragment), plus official Chinese renderings of US TV terms from the translated Douglas and Blum textbooks. Use when writing or judging a 国产剧, turning a novel or IP into a 30–50 episode drama, writing a 策划书 / 分集梗概 / 人物小传, formatting a Chinese teleplay, sizing episode count and word count, checking content red lines and the 立项/备案/审查 chain, reading a Chinese screenwriter contract, or mapping US series vocabulary onto Chinese usage.

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How episodic television actually gets made by a group (编剧室与制作现实) — merged from Goldberg & Rabkin (pitch as audition, leave-behind, cracking the story, beat sheet, notes discipline, production rewrites), Pamela Douglas (John Wells's room, staff-from-hell mistakes, the seven-rung ladder, step deal, the 14-day draft), Neil Landau's showrunner interviews (Lindelof, Mazzara, Katims, Bays), Evan Smith on sitcom staffing and roundtables, Richard Blum (dated), Kam Miller, and first-hand accounts by David Chase, Jesse Armstrong, Lucy Prebble, Aaron Sorkin, Julian Fellowes and Phoebe Waller-Bridge. Use when joining or running a writers' room, breaking an episode with a group, writing a leave-behind, beat sheet or outline on deadline, pitching episode ideas to an existing series, writing a spec episode, taking or giving notes, rewriting because of money, actors or locations, choosing between a staffed room and a single-author process, or asking 什么是 showrunner／编剧室怎么运作／怎么接 note.

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Assemble a submission-ready replication package to the AEA Data and Code Availability Standard (DCAS) / openICPSR / Social Science Reproduction Platform expectations — standard replication README, dataset manifest, computational-requirements capture, a Table/Figure → script:line map, and a confidential-data deposit plan. Use when user says "build the replication package", "prepare the openICPSR deposit", "make the AEA data and code package", "DCAS compliance", "assemble the deposit for the journal", or after a paper is accepted and the journal's data editor needs the package. NOT a numeric verifier — it calls /audit-reproducibility to confirm claims reproduce before packaging.

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AI DevKit · Test-driven development — write a failing test before writing production code. Use when implementing new functionality, adding behavior, or fixing bugs during active development.

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AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).

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Edit any video by conversation. Transcribe, cut, color grade, generate overlay animations, burn subtitles — for talking heads, montages, tutorials, travel, interviews. No presets, no menus. Ask questions, confirm the plan, execute, iterate, persist. Production-correctness rules are hard; everything else is artistic freedom.

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