「deep」の検索結果

Raise real concurrency in asyncio LLM batch scorers built on the OpenAI SDK (AsyncOpenAI, including OpenAI-compatible providers like DeepSeek). Use when: (1) raising an asyncio.Semaphore above ~100 produces no throughput gain, (2) a batch pipeline saturates near 100 in-flight requests despite a larger semaphore, (3) planning a high-concurrency campaign against a provider with no hard rate limit (DeepSeek v4-flash tolerates 2000+ in flight). Root cause: AsyncOpenAI's default httpx pool caps max_connections at 100, silently bottlenecking any larger semaphore — you must pass a custom http_client with httpx.Limits sized to the semaphore.

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Gate resumption of any multi-day LLM batch-scoring campaign that calls an unpinned model alias (deepseek-chat, gpt-*-latest, gemini-*-preview, any provider alias without a pinned version). Use when: (1) resuming a paused or credit-exhausted scoring run days after its last chunk, (2) topping up credits to finish a campaign, (3) extending a cached scoring pipeline with new items. Prevents silently splicing two model versions or serving revisions into one measure. Verified 2026-07-16: for $0.30 caught a serving-revision drift WITHIN DeepSeek v4-flash (same alias, same family, litigation scores systematically shifted across a 2-day gap) before an $83 resume spend.

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。

Run a deep code review across the manifold-csg crates

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Comprehensive guide for visualizing ENCODE data including deeptools heatmaps, IGV screenshots, UCSC track hubs, and publication-quality plots. Use when users need to create visualizations of ChIP-seq signal, peak landscapes, genome browser views, or any visual representation of ENCODE data. Trigger on: heatmap, visualization, genome browser, track hub, IGV, deeptools, signal plot, peak visualization, profile plot, publication figure, bigWig visualization.

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Guidance for Tauri v2 deep-linking plugin with URL schemes and safe routing.

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Build with DeepSeek's models — efficient open-weight reasoning models and low-cost API inference.

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 with DeepSeek Coder — open code models with strong reasoning and long-context code understanding.

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Affordable serverless GPU inference on DeepInfra — broad open-model catalog with straightforward pricing.

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Plan and protect deep work: scheduling focus blocks, task selection, shutdown rituals, and measuring depth. Use when important work never gets sustained attention or days fill with shallow tasks.

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Run a bounded, source-grounded research loop, draft a cited dossier, and optionally propose a separately reviewed canonical vault merge. Use when the user wants autonomous or deep research that may access the public web. Triggers: /autoresearch, autoresearch, research this topic, deep dive into, investigate, find everything about, research and file, go research, build a wiki on.

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Manage persistent coding sessions across Claude Code, Codex, Antigravity (agy), Grok Build, and OpenCode engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, autoloop autonomous workspace iteration, ultraapp building deployable web apps from a structured Q&A interview, switching models/tools at runtime, exposing the orchestrator's 78 tools as an MCP server to Hermes Agent / Claude Desktop / Cursor / Cline / Continue / Zed / Windsurf / Goose, or running as an Agent Client Protocol (ACP) agent that Zed / JetBrains / Neovim / Emacs / VS Code / dsh can drive directly. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "autoloop", "ultraapp", "Forge tab", "build a web app", "one-click app", "AppSpec", "autonomous iteration", "iterate until goal", "auto research", "switch model", "hand off a session", "session handoff", "switch engine", "continue on codex", "continue on claude", "move this session to another engine", "multi-agent coding", "coding session", "session inbox", "grok session", "grok build", "opencode", "mcp server", "clawo-mcp", "hermes mcp", "model context protocol", "ultracode", "dynamic workflow", "fanout", "fan-out", "best-of-N", "steer turn", "interrupt turn", "fork thread", "rollback turns", "acp", "agent client protocol", "clawo acp", "zed agent", "jetbrains agent", "external agent", "dsh subagent", "deepseek harness", "clawo runs", "run ledger", "session cost", "coding-agent token usage", "spend cap", "budget limit", "maxBudgetUsd", "durable workflow", "resume a run", "verify a coding run", "acceptance contract", "evidence bundle", "did the agent's tests actually pass", "protected tests", "agent edited the tests", "human gate", "repair loop", "clawo workflow", "clawo verify", "clawo solve", "clawo fanout", "fix and verify", "solve from the terminal".

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Use this skill when configuring, extending, or troubleshooting the Salesforce Field Service (FSL) Mobile app for field technicians — including offline priming strategy, app extensions, deep linking, and custom branding. Trigger keywords: FSL mobile, Field Service mobile app, offline priming, mobile extension toolkit, app extensions for field service. NOT for coding the LWC quick action or offline extension itself — use apex/fsl-mobile-app-extensions. NOT for technician job lifecycle, signature capture, or parts consumption — use admin/fsl-mobile-workflow-design.

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Expert in Japanese honorific language covering 尊敬語・謙譲語・丁寧語 with deep understanding of situational usage, business contexts, and cultural nuances

Enter explore mode for technical work — a thinking partner for {{engine_name}} code, architecture, and implementation decisions before you write any code. Use it to investigate a technical solution, design the architecture of a feature, choose between frameworks or libraries, compare implementation approaches, analyze how existing code or a system works, or deeply root-cause a complex bug without fixing it yet. The ultra mode adds adaptive artifacts (a C4 view, ADRs, a dependency graph) to the research folder — run it on "ultra research", "ultra explore" or "ultraresearch"; otherwise run the default. Trigger on "let's explore this technical solution", "how should we architect this feature", "which framework should we use", "run an ultra research on the save system", "investigate this error deeply". Research and analysis only — it never writes code. This is the CODE / engineering explorer — for GAME-DESIGN, GDD, mechanics, or balance research (no code) use /unikit-gd-explore.

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Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.

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Use when reviewing a codebase for architectural friction, shallow modules, poor test seams, scattered behavior, duplicated orchestration, or opportunities to deepen modules before implementing a ticket or workflow.

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为 OpenClaw 配置硅基流动 (SiliconFlow) 作为模型源。SiliconFlow 是国内领先的 AI 模型推理平台，提供 98+ 个 chat 模型，包含多个免费模型（Qwen3-8B、DeepSeek-R1-8B 等）。使用标准 OpenAI 协议（openai-completions）。包含 provider 注册、模型定义、别名配置、fallback 链接入和验证的完整流程。当管理员说想"加硅基流动"、"配 SiliconFlow"、"接入 SF 模型"、"加 Kimi"、"加 Qwen3"、"加免费模型"、"接入 DeepSeek V3.2"时使用此 skill。

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Surfaces architectural friction and proposes deepening refactors (shallow to deep modules). Renders via mk:preview. NOT for debate (mk:party); NOT for plan critique (mk:plan-ceo-review).

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Use when refining a draft user prompt before sending it to a coding agent. Decomposes goal/context/constraints/acceptance/output-format, detects ambiguity and model-coupled framing, then emits a model-agnostic rewrite. Supports --analyze, --score, and --deep. NOT for prompts from scratch (mk:brainstorming), plans/reviews (mk:elicit), implementation plans (mk:plan-creator), or general codebase scouting (mk:scout).

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Discovers de novo motifs and tests known motif enrichment in ChIP-seq, ATAC-seq, or other peak sequences using HOMER, MEME-ChIP (STREME, CentriMo, TOMTOM, FIMO), monaLisa, and AME. Handles background selection (GC-matched, dinucleotide-shuffled, Markov order-2, peak-flanks), motif databases (JASPAR 2024 CORE PWMs, JASPAR 2026 deep-learning collection, HOCOMOCO v12, HOMER built-in), centrally-enriched motif testing, and differential motif analysis. Use when identifying TF binding motifs in peaks, testing for known TF enrichment, scanning for motif instances, comparing motif content between conditions, or interpreting motifs from deep learning models.

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Perform a deep architectural analysis or security review requiring extended reasoning. Use for complex architecture decisions, security audits, or when standard analysis is not finding the root cause.

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Subagent flow for deep-reading GitHub issues + their linked/closing PRs to the bottom. Captures CURRENT state, maintainer status updates, reporter repro, blocking reviewer concerns, hidden second bugs, cross-repo duplicates. Invoked by weekly-report orchestrator; runs as a general-purpose subagent so the orchestrator's context stays small.

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Expert-level computer vision for robotics covering camera models, feature detection, object detection, pose estimation, visual SLAM, and deep learning for perception.

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Expert-level neural engineering covering neural interfaces, brain-computer interfaces, neural signal processing, deep brain stimulation, and neuroprosthetics.

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。