「production」の検索結果

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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。

The way to answer "how are my production AI agents doing?" and to run the team's agent-observability deployment — reach for it even on casual phrasing that names no tool. Trigger when the user wants to: • inspect agent telemetry — did agents error/fail/go flaky; sessions, events, latency, token usage, slowest models; eval/quality scores and whether quality dropped; • operate the deployment — ack/assign/resolve/mute/dismiss issues (alerts, reports, and audit findings) with notes; run and triage audits; see who has access and change roles (e.g. read-only); create or scope API keys (e.g. a push-only CI key); change settings; run saved or ad-hoc ClickHouse queries. Served by the `fp` CLI against FailproofAI Cloud. NOT for writing or designing an evaluator service / scoring logic (that's `agenteye-evaluator`), adding SDK/instrumentation to your app (that's `failproofai-sdk`, imported as `failproofai_sdk`), debugging the collector/daemon, or unrelated dev work (why a build/CI run failed, rotating non-FailproofAI Cloud secrets).

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。

Production-ready CSS transitions for web apps. Use when implementing notification badges, dropdowns, modals, panel reveals, page transitions, card resizes, number pop-ins, text swaps, icon swaps, success checks, avatar group hovers, error state shakes, search/input clear, skeleton loaders, shimmer text, sliding tabs, tooltips, staggered text reveals, card hover tilt, plus-to-menu morph, accordions, toasts, like buttons, learn-more hovers, checkbox checks, spinning counters, toggles, AI thinking states, reasoning streams, streaming text, matrix dot loaders, or banner stacking. Triggers on "add a transition", "animate the dropdown", "make the modal open smoothly", "swap icon", "page slide", "stagger animation", "open / close transition", "make it animate", "fade between", "success animation", "form error", "shake on invalid", "hover lift", "avatar stack hover", "clear the search", "skeleton loader", "loading shimmer", "shimmer text", "sliding tabs", "segmented control", "tooltip", "reveal text", "tilt card", "3D hover tilt", "cursor glare", "plus to menu", "FAB morph", "accordion", "collapsible", "expand / collapse", "disclosure", "toast", "snackbar", "like button", "heart animation", "learn more arrow", "checkbox", "check animation", "spinning counter", "odometer", "slot machine digits", "toggle", "switch", "thinking states", "AI status line", "agent reasoning", "reasoning stream", "streaming text", "stream words in", "matrix loader", "dot loader", "banner stack", "stacked toasts". Also "motion tokens", "scan for ad-hoc transitions", "replace hardcoded durations with motion tokens", "tokenize my animations", and the commands transitions reveal, transitions review, transitions apply, transitions refine.

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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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。

Bugcrowd-specific reporting tactics complementing report-writing: VRT category search-and-fallback strategy when no exact match exists, manual severity override when VRT defaults underrate impact, severity-request paragraph as first body section, OOS-clause rebuttal templates (rate limiting on auth-flow endpoints, debug-info framing, user-enumeration with sensitive PII, theoretical-issue counter), chained-finding cross-reference patterns, target selection for QA-vs-prod programs, researcher-side hygiene (Bugcrowdninja email alias, account state restoration, friendly-tester posture). Use when filing a Bugcrowd submission, when VRT default seems wrong, when triager closes as OOS or downgrades severity, when chaining linked submissions, or when scope distinguishes production from QA. Pairs with report-writing and triage-validation.

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。

Structure prediction using OpenFold3, an open-weights PyTorch reproduction of AlphaFold3 from the AlQuraishi Lab. Use this skill when predicting protein/nucleic-acid/ligand complex structures with an Apache-2.0-licensed AF3 reimplementation.

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。

Production-ready CI/CD configurations for Playwright — GitHub Actions, GitLab CI, CircleCI, Azure DevOps, Jenkins, Docker, parallel sharding, reporting, code coverage, and global setup/teardown.

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 "create bash scripts", "automate Linux tasks", "monitor system resources", "backup files", "manage users", or "write production shell scripts". It provides ready-to-use shell script templates for system administration.

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 building Next.js 14+ applications with App Router, server components, or server actions. Invoke for full-stack features, performance optimization, SEO implementation, production 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。

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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。

Production-grade Bayesian causal inference with PyMC, CausalPy, and DoWhy. Enforces DAG-first thinking, mandatory user checkpoints for assumptions, design-specific refutation, and defensible reporting with causal language guardrails. Trigger on: causal inference, causal effect estimation, treatment effects, counterfactuals, difference-in-differences (DiD), synthetic control, regression discontinuity (RDD), interrupted time series (ITS), instrumental variables (IV), propensity scores, DAGs, causal graphs, confounders, backdoor criterion, do-calculus, interventional distributions, pm.do(), pm.observe(), CausalPy, DoWhy, mediation analysis, refutation, sensitivity analysis, parallel trends, placebo tests, or any question of the form "does X cause Y" or "what is the effect of X on Y."

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 scalable programmatic SEO page templates with title patterns, internal linking logic, schema markup, and thin content avoidance strategies. Use when given a niche and data source to build page templates, establishing programmatic SEO structure, or scaling content production with templates. Platform: Google.

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。

Gate new or changed tests, and audit existing tests for low value, implementation coupling, duplication, and the test-only production seams they keep alive. Use when writing, changing, reviewing, or sweeping tests.

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 Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.

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 Iris to submit, inspect, debug, monitor, or recover jobs and tasks; diagnose scheduling and federation; deploy controllers; or reserve dev GPUs and TPUs. Use for ordinary Iris operations, including babysitting a job, controller rollouts, accelerator sessions, and stuck CoreWeave pods. Use a narrower production-run or Zephyr skill when that workflow is explicitly requested.

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。

Launch, resume, monitor, hand off, or seal an explicitly requested production-critical Marin run, normally at least 1e22 FLOPs.

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 to generate well-branded interfaces and assets for fast-agent, either for production or throwaway prototypes/mocks/etc. Contains essential design guidelines, colors, type, fonts, assets, and UI kit components for protoyping.

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。

Triage backlog, scan open issues, rank what to tackle first, or which PRs are production-ready.

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 or evolve a complex agent-enabled Tutti workspace app repository. Use for Tutti apps with web/server/shared monorepos, @tutti-os/agent-acp-kit local agent runtimes, kit-owned TUTTI_CLI agent/composer discovery, dynamic agent catalogs, run-scoped MCP tool gateways, app-owned package builders, web-first debugging, i18n harnesses, and production package validation. For simple package creation or repair, use tutti-workspace-app-factory instead.

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 a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing.

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。

Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.

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。

Review chart choice, labeling, accessibility, and storytelling quality for existing visualizations. Use as an explicit/manual helper for critique and cleanup, not as the main owner for scientific figure production or general chart generation.

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 the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.

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。

World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference 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。