「exec」の検索結果

Build, run, debug, and operate applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments that run inside a container with up to 8-hour lifetimes. Triggers on: Lambda MicroVMs, Firecracker isolation, snapshot-resumable compute, suspend/resume, sandboxed or untrusted code execution, AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, isolated security scanners, long-lived sessions, or port-listening servers (gRPC, WebSocket, custom TCP). For standard event-driven Lambda functions, use the aws-lambda skill instead.

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Determines whether a specific AI-agent action, output, recommendation, or proposed commitment remains admissible for execution or institutional reliance under current authority, delegated scope, evidence, facts, policy, risk, escalation, and revocation conditions. Use this Skill before an enterprise or regulated AI agent executes, updates records, triggers workflows, communicates externally, or before an institution relies on an agentic output in a way that creates consequence.

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Use ONLY when calling the `browser_execute` tool or driving a real browser via the Chrome DevTools Protocol. Required reading before the first `browser_execute` call in a session. Covers the three connection methods (local Chrome with remote debugging, isolated debug-port profile, Browser Use cloud), the in-process `session` / `console` snippet model, attaching to a page target, common CDP commands, the per-project `.bcode/agent-workspace/` for reusable scripts, and screenshot auto-attachment.

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Phase 3 of the prd-taskmaster pipeline: smart mode selection and user handoff. Detects installed capabilities (superpowers, ralph-loop, task-master-ai, playwright, research providers), recommends ONE execution mode (A/B/C) with reasoned justification, appends the task-execution workflow to CLAUDE.md, surfaces a structured AskUserQuestion multi-option picker for user agency, and dispatches the chosen mode. Mode D (Atlas Fleet) is selectable only when detect_capabilities returns tier=premium (licensed atlas-launcher detected); otherwise it is a locked Atlas Pro teaser. Plan Mode is NOT used (spec section 13.5): AskUserQuestion is the sole user-agency mechanism. Declares HANDOFF complete so EXECUTE can follow.

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Phase execution skill for licensed Atlas Fleet runs. Use when HANDOFF has selected Atlas Fleet and the project should be executed across isolated launcher worktrees with inbox-based result collection, verified CDD cards, sequential integration merges, and one final PR.

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Execute exactly one eligible Unit in an existing research Workspace; use for stepwise or manual semantic execution when status, Attempt, Artifact, Manifest, checkpoint, and acceptance evidence must remain synchronized.

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Create concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats for senior audiences.

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Autonomous goal execution — give a goal, get a plan, confirm, execute, report. You steer, Claude drives.

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Rewrite an exec update, memo, strategy doc, deck outline, Slack post or talk so it lands with senior people, and get a graded score plus the top 3 fixes. Use when you say 'rewrite this for my VP', 'exec update', 'how do I present to the CEO', 'my memo is too long', 'prep me for this review', 'all-hands talk' or 'I get nervous presenting'. Draws on 296 insights from 90 Lenny's Podcast guests incl. Wes Kao, Nancy Duarte and Matt Abrahams.

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Orchestrate coding work by delegating well-specified implementation tasks to xAI's Grok Build CLI (grok) running headlessly, while the coding assistant plans, writes the task specs, reviews every diff, and owns the result. Use when user says: 'use grok', 'grok build', 'delegate to grok', 'have grok implement', 'have grok execute', 'have grok build', 'send to grok', 'execute this plan with grok'. Executes a Markdown implementation plan task-by-task, or ad-hoc tasks with an inline spec.

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Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

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Execute an implementation plan file produced by $draft-plan or $turboplan. Runs pre-implementation prep, then runs $implement to execute the steps and finalize once they are all done. Use when the user asks to "implement plan", "implement the plan", "execute the plan", "run the plan", "implement plans/<slug>.md", "start implementing the plan", or starts a fresh session to implement a previously drafted plan.

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。

Execute an implementation plan file produced by /draft-plan or /turboplan. Runs pre-implementation prep, then runs /implement to execute the steps and finalize once they are all done. Use when the user asks to "implement plan", "implement the plan", "execute the plan", "run the plan", "implement plans/<slug>.md", "start implementing the plan", or starts a fresh session to implement a previously drafted plan.

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Execute structured task plans with status tracking. Use when the user provides a plan file path in the format `plans/{current-date}-{task-name}-{version}.md` or explicitly asks you to execute a plan file.

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Provides patterns for unit testing Spring `@Scheduled` and `@Async` methods using JUnit 5, CompletableFuture, Awaitility, and Mockito. Covers mocking task execution and timing, verifying execution counts, testing cron expressions, validating retry behavior, and simulating thread pool behavior. Use when testing background tasks, cron jobs, periodic execution, scheduled tasks, or thread pool behavior.

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Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.

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Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.

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Use ExecuTorch to export PyTorch models to edge runtime artifacts, build host/device runtimes, choose delegates, profile/debug execution, and operate specialized Qualcomm, Cortex-M, LLM, and binary-size workflows.

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Guides privacy program effectiveness measurement including leading and lagging indicators, KPI definition, benchmarking methodology, executive reporting formats, board-level privacy dashboards, and metric-driven program improvement. Covers operational, compliance, risk, and strategic privacy metrics across the program lifecycle. Keywords: privacy metrics, KPIs, benchmarking, executive reporting, dashboard, program effectiveness.

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Creates executive reporting and visualization from RoPA data including processing activity counts, risk heatmaps, compliance scores, trend analysis, and supervisory authority readiness indicators. Activate for RoPA dashboard, executive reporting, risk heatmap, compliance score, trend analysis, board reporting, KPI.

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Guides privacy audit report writing including executive summary drafting, findings classification (critical, high, medium, low), evidence referencing, root cause analysis documentation, recommendation formulation, management response tracking, and report distribution protocols. Covers report structure from scope definition through appendices and sign-off. Keywords: audit report, findings documentation, executive summary, recommendations, report structure, privacy audit deliverables.

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Master go-to-market strategy, launch planning and execution, sales enablement, and marketing campaigns. Execute successful product launches.

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Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.

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Instruments programs to record execution information for deterministic replay debugging. Use when debugging hard-to-reproduce bugs (race conditions, timing issues, intermittent failures, heisenbugs), reproducing production failures, or analyzing complex execution sequences. Records non-deterministic events (I/O, threading, randomness, time) to enable exact replay of program executions. Supports Python, JavaScript, Java, and C/C++ with both custom instrumentation and existing replay tools.

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。