「method」の検索結果

Detect horizontal gene transfer (HGT / LGT) using compositional methods (GC%, codon usage, tetranucleotide z-scores via SIGI-HMM, AlienHunter, IslandViewer 4, IslandPath-DIMOB), phylogenetic-incongruence methods (AvP, HGTphyloDetect, ALE / GeneRax / AleRax reconciliation, RANGER-DTL), and BLAST-distribution methods (HGTector v2, DarkHorse, Alien Index). Use when screening prokaryote genomes for genomic islands and HGT events, distinguishing HGT from incomplete lineage sorting / differential gene loss / hybridization, mapping donor lineages via phylogenetic placement, separating eukaryotic HGT from contamination, ruling out gBGC as a false signal, or quantifying DTL rates with ALE/GeneRax on bacterial trees.

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Cross-method decision tree for calling hits in pooled CRISPR screens. Catalogs statistical models (MAGeCK RRA, MAGeCK MLE, BAGEL2, drugZ, JACKS, Chronos, CERES), experimental designs each is built for, failure modes outside design domain, reconciliation when methods disagree, multiple-testing and effect-size thresholds, the order of operations (count -> QC -> CN-correct -> hit-call -> validate), the second-best-sgRNA conservative rule, and consensus-hit strategy. Use when choosing among MAGeCK / BAGEL2 / drugZ / JACKS / Chronos for a given design, reconciling disagreement across two or three methods on the same screen, deciding whether to require consensus, gating downstream validation by hit-confidence tier, or interpreting unstable hit lists across reruns.

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。

Detect horizontal gene transfer (HGT / LGT) using compositional methods (GC%, codon usage, tetranucleotide z-scores via SIGI-HMM, AlienHunter, IslandViewer 4, IslandPath-DIMOB), phylogenetic-incongruence methods (AvP, HGTphyloDetect, ALE / GeneRax / AleRax reconciliation, RANGER-DTL), and BLAST-distribution methods (HGTector v2, DarkHorse, Alien Index). Use when screening prokaryote genomes for genomic islands and HGT events, distinguishing HGT from incomplete lineage sorting / differential gene loss / hybridization, mapping donor lineages via phylogenetic placement, separating eukaryotic HGT from contamination, ruling out gBGC as a false signal, or quantifying DTL rates with ALE/GeneRax on bacterial trees.

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。

Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing,...

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Structured OSINT methodology framework: target definition, source selection, collection workflows, data correlation, timeline reconstruction, and reporting. Use to guide systematic OSINT campaigns or teach OSINT methodology.

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Detect method clobbering via user-controlled object keys that overwrite built-in methods like toString, valueOf, or hasOwnProperty, causing crashes or logic bypass.

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学術・技術文献を検索し、選定基準に沿って比較・統合するスキルです。検索履歴や除外理由を残し、根拠の強さと引用を確認したレビューにまとめます。

• 研究テーマの全体像を把握したいとき
• 検索手順を記録した文献レビュー
• 研究結果の矛盾や未解決課題の整理

複数店舗の販売データや商品の特性をもとに、需要予測、安全在庫、発注量を検討するスキル。販促後の需要減少や季節商品の値下げ時期まで計画を支援します。

• 商品ごとの需要予測方法の選定
• 仕入れ先の納期変更に伴う安全在庫の見直し
• 販促中と終了後の需要を見積もりたいとき

採点済みの競合情報を、市場マップや比較表、差別化の余地、優先施策を含むレポートにまとめます。経営層への報告や、チームで競争方針を決める場面に役立ちます。

• 経営層や取締役会向けの競合報告
• 完成済み競合プロフィールの統合
• 差別化の余地と競合脅威の検討

自社の強みや顧客像を基に、比較すべき競合と調査先を選びます。直接競合・周辺競合・目標となる企業に分類し、根拠付きの候補一覧を作って詳しい比較の準備を整えます。

• 競合比較の対象を決めたいとき
• 直接競合・周辺競合・目標企業の分類
• 市場調査レポートの候補を絞りたいとき

重みが公開されたLLMの回答拒否に関わる仕組みを分析し、再学習なしで重みを変更する実験を支援。計算環境に合うモデルや手法の選択、変更前後の品質評価まで扱います。

• LLMの回答拒否の仕組みを調べたいとき
• 再学習せず重み変更を実験したいとき
• 計算環境に合うモデルと手法を選びたいとき

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

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Use when reviewing scripts, client components, bundles, or runtime behavior related to Use modern array and object methods. Inspect both source code and the browser execution path so fixes target the real bottleneck or bug.

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Test a product concept with Amazon's Working Backwards method: write the press release for the finished product first, then answer hard customer and stakeholder questions, ending in a complete PRFAQ document. Use when the user requests to 'create a PRFAQ', 'work backwards', or 'run the PRFAQ challenge'

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Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team

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。

Required bmod metadata. Never invoke this skill.

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Binance Onchain Pay enables users to buy cryptocurrency with fiat (e.g., EUR, USD) or send existing crypto from their Binance account directly to any external on-chain wallet address in a single flow—no manual withdrawal needed. Enables partners to integrate crypto buying services: - payment-method-list: Get available payment methods (Card, P2P, Google Pay, Apple Pay, etc.) with limits for a fiat/crypto pair - trading-pairs: List all supported fiat currencies and cryptocurrencies - estimated-quote: Get real-time price quote including exchange rate, fees, and estimated crypto amount - pre-order: Create a buy order and get redirect URL to Binance payment flow - order: Query order status and details (processing, completed, failed, etc.) - crypto-network: Get supported blockchain networks with withdraw fees and limits - p2p/trading-pairs: List P2P-specific trading pairs

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PluginEval quality methodology, covering dimensions, rubrics, and scoring formulas. Use this skill when understanding how plugin quality is measured, when interpreting a low score on a specific dimension, when deciding how to improve a skill's triggering accuracy or orchestration fitness, when setting score thresholds for your marketplace, or when explaining quality badges to external partners like Neon.

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Look up Microsoft API references, find working code samples, and verify SDK code is correct. Use when working with Azure SDKs, .NET libraries, or Microsoft APIs—to find the right method, check parameters, get working examples, or troubleshoot errors. Catches hallucinated methods, wrong signatures, and deprecated patterns by querying official docs.

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Refactoring using Extract Methods in Java Language

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Conduct a defensible cybersecurity risk assessment using the NIST SP 800-30 Rev 1 methodology: prepare scope and a risk model, identify threat sources and threat events, identify vulnerabilities and predisposing conditions, determine likelihood and impact, compute risk, and communicate results as a prioritized risk register. Use when an organization needs an actual risk *assessment* (not a maturity score), when a control framework (CSF, ISO 27001, RMF, SOC 2, PCI) requires a documented risk analysis as input, when leadership asks "what are our top risks and how bad are they", when assessing risk for a new system or major change, or when building a risk register from scratch. This is the methodology that feeds framework selection, ATO packages, and treatment decisions. Keywords: risk assessment, NIST 800-30, threat modeling, likelihood and impact, risk register, risk analysis, threat sources, vulnerabilities, risk determination, qualitative risk, risk matrix, residual risk, risk treatment.

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Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD contract, when a contract carries DFARS clause 252.204-7012/7019/7020/7021, when preparing for or responding to a CMMC assessment, when computing or improving an SPRS score, when building a System Security Plan or POA&M for 800-171, or when scoping which systems are in the CUI boundary. Keywords: CMMC, CMMC Level 2, NIST 800-171, SP 800-171 Rev 2, CUI, FCI, SPRS, DFARS 7012, C3PAO, POA&M, System Security Plan, DoD Assessment Methodology, 110 controls, defense industrial base, DIB, FedRAMP equivalency.

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Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when generating synthetic user scenarios, evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.

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External research synthesis from Trail of Bits, SlowMist, ConsenSys, Immunefi, and Cyfrin. Use this for advanced audit methodology, Echidna/Medusa fuzzing setup, Slither custom detector writing, attack pattern deep dives, or the 4-phase learning roadmap.

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。