'execution' 검색 결과

Windows アプリ開発 (Windows AI Foundry) の AI/ML 統合リファレンス。 Windows AI APIs、LanguageModel, TextRecognizer, ImageScaler, ImageObjectExtractor, ImageObjectRemover, ImageDescriptionGenerator, SemanticSearch, ContentModeration、 Phi Silica / Aion Instruct、LoRA、Windows ML、Windows ML Runtime API、ONNX Runtime、 execution providers、WebGPU EP、Model Catalog、LearningModel、 Foundry Local (CLI / REST API / SDK)、MCP サーバー、App Actions、IActionProvider、 Agent Launchers、DirectML、IDMLDevice、operators、tensors、NPU。

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Upstash サーバーレスデータプラットフォーム (マネージド SaaS の JS SDK)。 @upstash/redis (REST, pipelining, transactions, JSON, Redis Search, VECTOR/Array/Functions コマンド)、 @upstash/ratelimit (Fixed/Sliding Window, Token Bucket, blockUntilReady)、 QStash (publishJSON, schedules, queues, URL Groups, flow-control, DLQ)、 @upstash/vector (upsert, query, ANN, namespace, hybrid/sparse index, embedding models, reranking)、 @upstash/workflow (serve, durable execution, context.run/sleep/call/invoke, waitForEvent, parallel steps, agents)、 Upstash Search (@upstash/search, search, upsert, fetch, range, filtering, reranking, algorithm)、 @upstash/box (サンドボックス, filesystem, git, CDP, browser, network policy, snapshots, custom harness)、 upstash CLI。Rust 製 fandhe-db とは別。

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Inngest イベント駆動 Durable Execution リファレンス。バックグラウンドジョブ、長時間ワークフロー。 createFunction, step.run, step.sleep, step.waitForEvent, step.waitForSignal, step.invoke, step.sendEvent, step.sleepUntil, step.fetch, step.ai.infer, step.ai.wrap, step.metadata, inngest.send, serve, connect, checkpointing, Inngest CLI。 concurrency, throttle, debounce, rate-limit, batching, priority, idempotency, singleton, multi-tenancy フロー制御。 Realtime（channels, topics, publish, subscribe, subscription tokens, useRealtime）、 Agent Evals（scoring, group.experiment）、MCP（Dev Server / Cloud）。 デプロイ先 Next.js, Express, Hono, Cloudflare Workers, Vercel, Netlify, DigitalOcean, Render。

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Claude API (platform.claude.com) の tool use / Agent Skills / MCP。 tool definition (JSON Schema), tool_use / tool_result, server tools（code execution, web search, web fetch, memory tool, tool search）, client toolset（computer use, browser use）, Agent Skills (SKILL.md), Skills API GA (/v1/skills), MCP connector, mcp_servers, mcp_tool_listing, MCP tunnels, Tunnels API。

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Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.

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Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.

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AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g

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XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.

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Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

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Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.

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Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb. Load this skill when the task involves exploration, iteration, or inspecting intermediate results — data science, ML experimentation, API exploration, or building up complex code step-by-step. Uses terminal to run CLI commands against a live Jupyter kernel. No new tools required.

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The PRIMARY development workflow for the Archon project (remote-coding-agent). Use this skill instead of any PRP skills when working on Archon code. Routes to 10 specialized cookbooks based on what the user is trying to do: RESEARCH — "how does the orchestrator work?", "where is session state defined?", "trace the workflow execution flow", "what is IWorkflowStore?" INVESTIGATE — "should we use Drizzle or Prisma?", "what's the best way to add WebSockets?", "can we migrate to Turso?", "how do other projects handle rate limiting?" PRD — "write a PRD for dark mode", "spec out the notification feature", "product requirements for webhook retry" PLAN — "plan the auth refactor", "design the caching layer", "create an implementation plan for #42" IMPLEMENT — "implement the plan", "execute .claude/archon/plans/auth.plan.md", "build the feature from the plan", "code this up" REVIEW — "review PR #123", "review my changes", "code review the diff" DEBUG — "debug the failing test", "why is streaming broken?", "root cause analysis on the timeout issue" COMMIT — "commit these changes", "commit the auth refactor" PR — "create a PR", "open a pull request for this branch" ISSUE — "report this to gh", "create a gh issue", "log it in github", "file a bug for this", "create a feature request" This skill triggers on ANY development task: researching, investigating, planning, building, reviewing, debugging, committing, or shipping code. NOT for: Running Archon CLI workflows in worktrees (use /archon instead).

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Base skill for Refly ecosystem: creates, discovers, and runs domain-specific skills bound to workflows. Routes user intent to matching domain skills via symlinks, delegates execution to Refly backend. Use when user asks to: create skills, run workflows, automate multi-step tasks, or manage pipelines. Triggers: refly, skill, workflow, run skill, create skill, automation, pipeline. Requires: @refly/cli installed and authenticated.

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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

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Use when the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: "How does X work?", "What calls this function?", "Show me the auth flow"

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15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.

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Independent quality assurance for one SDD Composy task in qa_required: CA coverage, unit/integration/E2E, accessibility, responsiveness, environment, and evidence inventory, producing the QA report and requesting evidence_required. Use when a task finished execution — 'rodar o QA da task', 'testar a TASK-003', 'validar a implementação'. Do NOT use for code review (sdd-review), the final verdict (sdd-verify), or test runs outside an SDD task.

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Select traceable regression coverage from change impact, affected risks, criteria, dependencies, and prior defects rather than execution convenience.

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Use when a user asks for QA planning, execution, review, release assessment, reporting, status, or test-tool recommendations and the correct PWDEV QA workflow must be selected safely.

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Analyze a completed phase diff for high-confidence behavior-preserving simplifications and apply only explicitly approved proposals. Use after execution and before review to reduce duplication, dead code, needless complexity, or avoidable inefficiency.

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Decompose an approved PWDEV Flow specification into dependency-aware waves and atomic executable tasks. Use when design is approved and the user needs exact file scope, test-first actions, verification commands, and an execution gate.

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When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' 'ideas to grow,' 'what else can I try,' 'I don't know how to market this,' 'brainstorm marketing,' or 'what marketing should I do.' Use this as a starting point whenever someone is stuck or looking for inspiration on how to grow. For specific channel execution, see the relevant skill (paid-ads, social-content, email-sequence, etc.).

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Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan". Proactively suggest when the user has a plan or design doc and is about to start coding — to catch architecture issues before implementation. (gstack) Voice triggers (speech-to-text aliases): "tech review", "technical review", "plan engineering review".

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Strict routing mode for prompts prefixed with `(best)`. USE FOR: any turn where the user explicitly wants the safest, smallest-context, highest-discipline execution path. This skill must route into context-budget-guard first, then continue into the task-specific workflow.

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