'deep' 검색 결과

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

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Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

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Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

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PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

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Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

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Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

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Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

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Deep research on technical topics using EXA tools with intelligent two-tier caching. Use when user asks to research a topic, investigate best practices, look up information, find patterns, or explore architectures. Also invoked by /research command. Triggers: "research", "look up", "investigate", "deep dive", "find information about", "what are best practices for", "how do others implement".

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Design deployment-focused distillation systems that balance model size, accuracy, calibration, and cascade escalation under real resource limits. Best for teacher-student compression, threshold design, and failure-aware deployment. Activate on "model compression", "teacher- student", "distillation score", "cascade model", "edge deployment", or "model calibration". NOT for generic deep-learning overviews, prompt optimization, or training work without a concrete distillation objective.

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Deep analysis of knowledge distillation techniques for compressing large models into smaller efficient ones

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Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

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Visualises RNA-modification data with transcript-feature metagene plots (Guitar GuitarPlot; MetaPlotR; deepTools computeMatrix scale-regions), peak-centred heatmaps (ComplexHeatmap; deepTools plotHeatmap), IP-vs-input paired browser tracks (log2 IP/input bigWig via deepTools bamCompare; pyGenomeTracks; Gviz; IGV/UCSC track hubs), DRACH sequence-logo plots (ggseqlogo; MEME), feature-distribution stacked bars, and volcano/MA plots for differential modification. Establishes stop-codon enrichment in the metagene plot as the biological QC anchor for any MeRIP dataset (Dominissini 2012; Meyer 2012). Use when producing the canonical metagene plot with stop-codon enrichment as a QC anchor, building paired IP/input genome-browser tracks at single-locus resolution, plotting peak-centred heatmaps clustered by condition, summarising peak distribution across transcript features, generating DRACH motif logos as sanity checks, rendering volcano plots of differential m6A, or reproducing the stop-codon enrichment plot.

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Sequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or Enformer. Use when correcting Tn5 bias with neural networks beyond k-mer models, predicting per-base accessibility profiles, scoring in silico variant effects at GWAS or rare-variant SNPs, discovering motifs via DeepLIFT/TF-MoDISco from a trained model, or generating cell-type-specific accessibility predictions for unobserved cell states.

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Use when a decision needs deep multi-source technical research with cited evidence — technology evaluation, ecosystem comparison, standards/spec fact-finding, "how do others solve X". Triggers on "research X", "deep dive on X", "evaluate X vs Y", "find best practices for X". NOT for library/API doc lookup (see mk:docs-finder); NOT for one-shot URL fetch (see mk:web-to-markdown); NOT for internal codebase discovery (see mk:scout); NOT for project-only Q&A (see mk:ask-me); NOT for comparing solution designs (see mk:brainstorming); NOT for root-cause debugging (see mk:investigate); NOT for wiki ingestion of sources (see mk:wiki-research).

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Deep analysis of articles/long-form via thinking frameworks (SCQA, mental models, inversion) — 'analyze article', 'deep dive', 'extract insights', URL/text wanting depth not summary.

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Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

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Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

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Decision protocol for strategic work: recall the knowledge vault, run a gap analysis, emit a deep-research prompt for external tools, then synthesize the returned reports into a decision memo. Use before any new product, feature, market, pricing, GTM or architecture call, where local recall alone is not enough. Triggers: "/alfa-search-recall-deepresearch", "alpha protocol", "R+DR".

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Cursorで判断に迷う重要な論点を独立した熟考担当に検討させ、結論と未解決点を整理する。選択肢の比較や設計判断に確信を持てない場合に使う。要件をユーザーと決める場合は brainstorm、計画作成は deepplan。

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判断に迷う重要な論点を独立した熟考担当に検討させ、結論と未解決点を整理する。選択肢の比較や設計判断に確信を持てない場合に使う。要件をユーザーと決める場合は brainstorm、計画作成は deepplan。

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DeepSeek利用時の失敗切り分け、再試行、quota確認、provider選定を支援する。応答停止、tool call欠落、429などの症状で使う。

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