「execution」の検索結果

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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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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Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.

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Unified entry for all development intents — classify intent, assess complexity, route to the correct execution channel: /maestro-companion (lightweight), standard single run, or /maestro and /maestro-ralph (multi-step manual/orchestrated). Pure router, never runs execution loops itself

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This skill should be used when the user asks about "ralph arguments", "quick mode", "commit spec", "max iterations", "ralph state file", "prototype overlay", "execution modes", "ralph loop", "coordinator behavior", "delegate to subagent", or needs guidance on Ralph plugin arguments, state management, delegation patterns, or execution loop behavior. Core behavioral skill for all Ralph Specum operations.

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Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits frame extraction jobs on ingested media (StartExecution / Operation.Task.Snapshot), including specified time, fixed interval, specified frame, scene-change, sprite image, and output index modes. Trigger keywords: VOD frame extraction, frame extraction, extract frames, video snapshot, thumbnail, screenshot from video, StartExecution Snapshot.

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Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits precision erasure jobs on ingested media (StartExecution / Operation.Task.Erase): Auto OCR only — default subtitle-only erasure, optional full on-screen text, optional EraseOption ClipFilter (skip/selected); NewVid is always true; optional WithEraseInfo. Trigger keywords: precision erasure, precise erase, VOD upload, subtitle removal, OCR subtitles, remove on-screen text, erase text, StartExecution Erase.

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Use when reviewing Java enterprise evidence for MiFID II investment services, investment activities, client classification, suitability, appropriateness, order-handling evidence, best-execution evidence, algorithmic-trading governance evidence, market-access governance evidence, transaction evidence, record keeping, monitoring, or compliance-owner handoff. This should trigger for requests such as Review a Java investment-service platform for MiFID II evidence; Assess suitability, appropriateness, order-handling evidence, or best-execution evidence; Document audit, monitoring, or clock-synchronisation gaps for algorithmic-trading governance; Assess investment-service engineering evidence before production release. Part of Plinth Toolkit

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Use when reviewing whether an OpenSpec change's execution goal, acceptance criteria, and implementation or verification tasks are aligned. This should trigger for requests such as Review this OpenSpec change with ATDD; Check acceptance criteria against tasks; Find acceptance criteria without task coverage; Detect tasks that diverge from the execution goal; Explain what is missing, vague, ambiguous, partial, absent, or divergent in this OpenSpec change. Part of Plinth Toolkit

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

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Delegate complex, long-running tasks to Manus AI agent for autonomous execution. Use when user says 'use manus', 'delegate to manus', 'send to manus', 'have manus do', 'ask manus', 'check manus sessions', or when tasks require deep web research, market analysis, product comparisons, stock analysis, competitive research, document generation, data analysis, or multi-step workflows that benefit from autonomous agent execution with parallel processing.

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4-phase execution loop for work units - IMPLEMENT, VALIDATE, ADVERSARIAL REVIEW, COMMIT

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Solana DEX swap execution via Jupiter aggregator including quoting, transaction building, signing, and confirmation

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Reinforcement learning for trade execution optimization including order splitting, adaptive timing, and impact minimization

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This skill enriches vague prompts with targeted research and clarification before execution. Should be used when a prompt is determined to be vague and requires systematic research, question generation, and execution guidance.

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Use when building functions that must survive process crashes, retry automatically on failure, run on a schedule, react to events, or maintain state across infrastructure failures — e.g., webhook handlers that drop events, flaky cron jobs, background jobs that fail mid-execution, or workflows that need to resume where they left off. Covers Inngest function configuration, triggers (events, cron, invoke), step execution and memoization, idempotency, cancellation, error handling, retries, logging, and observability.

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Fetch trade executions from Interactive Brokers filtered by account, date range, or symbol. Supports live API (~7 days history) and FlexReport (full history). Use when user asks about their trades, executions, or transaction history. Requires TWS or IB Gateway running locally.

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Registers external services with health checks, central config, and unified execution. Use when integrating multiple external services needing coordination.

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Delegates execution to eight CLIs (Gemini, Qwen, MiniMax, GLM, Muse, Codex, OpenCode, Glimmer). Use for execution tasks. Do not use for secrets.

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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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Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.

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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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Analyzes test suites to identify redundant and duplicate test cases using coverage analysis, semantic similarity, and execution results. Use this skill when you need to reduce test suite size, identify redundant tests, optimize test execution time, analyze test coverage overlap, find tests with identical behavior, or improve test suite maintainability. Triggers when users ask to deduplicate tests, find redundant test cases, reduce test suite size, identify duplicate tests, or optimize test coverage.

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Collect, normalize, and structure execution traces from instrumented programs (strace, ltrace) into JSON format for downstream analysis. Use when working with system call traces, library call traces, or execution logs that need to be analyzed for debugging, test case reproduction, or verification. Supports parsing strace/ltrace output, filtering noise, extracting debug information, and preparing traces for bug analysis or reproduction workflows.

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。