「exec」の検索結果

Use after a phase executes, when the user wants to test the built features themselves. Runs one conversational UAT test at a time into {phase}-UAT.md and, when something fails, diagnoses it and queues fix plans for /gsd-execute-phase.

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Use when the user wants to execute a phase's plans, resume the remaining plans, or run only one wave. Discovers plans, groups them into dependency waves, spawns a fresh subagent per plan, then verifies the phase.

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Use when you have a written implementation plan to execute in a separate session with review checkpoints

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Execute multi-task implementation plans by dispatching a fresh implementer subagent per task with independent review gates. Use when implementing plans, executing multi-task PRs, or transitioning from planning to implementation.

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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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Iterative skill tuning via execute-evaluate-improve feedback loop. Uses maestro delegate Claude to execute skill, Agy to evaluate quality, and Agent to apply improvements. Iterates until quality threshold or max iterations. Triggers on "skill iter tune", "iterative skill tuning", "tune skill".

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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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Execute the implementation plan by processing and executing all tasks defined in tasks.md

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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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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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Launch and continue the Volcengine AI Research survey workflow for concept testing, audience design, questionnaire drafting, interview guide generation, execution confirmation, progress checks, and result queries. Use this skill when the user wants to create, revise, confirm, execute, or follow up on a real AI research survey task in ABCompass instead of doing generic brainstorming, copywriting, translation, summarization, or broad market discussion.

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Run one prompt through headless Codex and capture the result. Use when: wanting a one-shot `codex exec` run or CI step. Not for batches or retries.

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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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Use when you need to apply Java concurrency best practices — including thread safety fundamentals, ExecutorService thread pool management, concurrent design patterns like Producer-Consumer, asynchronous programming with CompletableFuture, immutability and safe publication, deadlock avoidance, virtual threads, structured concurrency, scoped values, backpressure, cancellation discipline, and observability for concurrent systems. This should trigger for requests such as Review Java code for concurrency; Review Java code for thread safety; Fix race conditions in Java concurrency code; Choose ExecutorService or virtual threads in Java; Improve synchronization and shared mutable state handling; Apply structured concurrency for related Java subtasks. Part of Plinth Toolkit

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Decision rubric for when an LM agent should write-and-run code (Program-of-Thought / code interpreter) versus reason in natural language: classify each step as deterministic- computable (emit + execute code, feed the result back) vs judgment (stay in prose). Use when designing or debugging an agent step that does arithmetic/parsing/data transforms, when prose reasoning hallucinates a computation (under-coding), or when a sandbox round- trip is wasted on a judgment task (over-coding). Search keywords: code interpreter, agent does math wrong, calculator hallucination, when to run code vs reason, program of thought, PoT, tool vs reasoning.

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Split a multi-call LM workflow by cognitive load, not by accuracy: let one strong model make the few reasoning decisions and a cheap model do the many mechanical executions (Aider architect+editor, DSPy optimizer-LM vs task-LM, vLLM speculative draft+target, LangGraph supervisor+worker are the same shape). Use when designing or cost-optimizing a pipeline that calls an LM many times, when deciding which steps need a strong reasoner vs a cheap executor, or when adding an escalation valve for when the cheap tier degrades. Search keywords: reduce LLM cost, cheaper model, lower token cost, model cascade, route to cheap model, strong model plus cheap model, LLM cost optimization.

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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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This skill should be used when analyzing binaries, executables, or bytecode to understand what they do or how they work. Triggers on "binary", "executable", "ELF", "what does this do", "reverse engineer", "disassemble", "decompile", "pyc file", "python bytecode", "analyze binary", "figure out", "marshal". Routes to sub-skills for triage, static analysis, dynamic analysis, synthesis, or tool setup.

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Use when you need to run a binary, trace execution, or observe runtime behavior. Runtime analysis via QEMU emulation, GDB debugging, and Frida hooking - syscall tracing (strace), breakpoints, memory inspection, function interception. Keywords - "run binary", "execute", "debug", "trace syscalls", "set breakpoint", "qemu", "gdb", "frida", "strace", "watch memory"

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

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Translate technical security work into the language of non-security audiences — board, executives, engineering, customer success, customers, legal, procurement, sales. Covers incident communication, post-mortem narrative, audit-findings-for-stakeholders, risk justification, security spend justification, and customer-facing breach disclosure. Use when the user mentions 'security comms,' 'communicate this finding,' 'explain to my boss,' 'board update,' 'executive summary,' 'incident communication,' 'breach notification,' 'customer disclosure,' 'security memo,' 'post-mortem narrative,' 'risk justification,' 'why this matters to the business,' 'translate this finding,' 'stakeholder update,' or has technical security work that needs to land with a non-security audience.

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Plan, scope, and execute an authorized red-team engagement — distinct from a penetration test. Covers engagement methodology, assumed-breach scenarios, ATT&CK emulation plans, rules of engagement, deconfliction with the blue team, post-engagement debriefs, and the program-level work that makes red teams actually improve defenses. Use when the user mentions 'red team,' 'red team engagement,' 'red teaming,' 'adversary emulation,' 'ATT&CK emulation,' 'assumed breach,' 'purple team exercise,' 'tabletop with technical execution,' 'red team scope,' 'rules of engagement,' 'red team RoE,' 'deconfliction,' 'red team debrief,' or wants to design or run a red-team engagement against systems with authorization.

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 you have a written implementation plan to execute in a separate session with review checkpoints

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。