「analysis」の検索結果

Deep exploration and synthesis workflow with dynamic planning and hub-and-spoke coordination. Use for deep analysis, codebase understanding, or thorough investigation of a focus area.

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。

Deep exploration and synthesis workflow with dynamic planning and hub-and-spoke coordination. Use for deep analysis, deep understanding, or codebase investigation.

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。

Synthesizes exploration findings into unified analysis with deep investigation capabilities (shell commands, git history, dependency analysis) and completeness evaluation (converted from agent)

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。

Deep exploration and synthesis workflow using agent teams with dynamic planning and hub-and-spoke coordination. Use when asked for "deep analysis", "deep understanding", "analyze codebase", "explore and analyze", or "investigate codebase".

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。

Produce a structured codebase analysis report with architecture overview, critical files, patterns, and actionable recommendations.

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。

Deep exploration and synthesis workflow using Agent Teams with dynamic planning and hub-and-spoke coordination. Use when asked for "deep analysis", "deep understanding", "analyze codebase", "explore and analyze", or "investigate codebase".

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。

Mobile (Android) app recon and analysis — decompile APK, extract secrets, find hardcoded endpoints, exposed Firebase / AWS / API keys, deeplink abuse, intent vulnerabilities, exported components, WebView XSS, MobSF static analysis. Use when target's scope includes Android apps (.apk).

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。

Extract endpoints, secrets, and hidden routes from JavaScript files using LinkFinder, SecretFinder, JSluice, and source-map analysis. Use when the user has live hosts and needs to mine the JS for attack surface that's not visible in the UI.

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。

Find the most valuable commercial insight and the monetization point closest to lawful revenue for a project, product, service, website, community, content account, open-source tool, or business idea. Use when a user asks how to monetize, who pays, why people do not buy, what to charge, whether to keep building, what to stop, what to do next, or asks to continue or deepen an earlier business analysis. Answer the user's actual question before asking for more information and carry the analysis forward without repeating it. When the buyer, purchased result, or delivery ability is unknown, do not select them from industry stereotypes; use explicit conditional candidates and an evidence-gathering next step. Not for investment advice, income forecasts, get-rich-quick schemes, or guaranteed results.

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。

Conduct structured insect behavior observations using sampling protocols, ethogram categories, event recording, interaction logging, environmental context, and summary analysis. Covers focal animal sampling, scan sampling, all-occurrences sampling, and instantaneous sampling methods. Defines a standard insect ethogram with locomotion, feeding, grooming, mating, defense, communication, and rest categories. Includes timestamped event recording, intraspecific and interspecific interaction logging, environmental covariate documentation, and time budget analysis. Use when studying insect behavior for ecological research, documenting behavioral repertoires for a species, observing pollinator activity or predator-prey dynamics, or supporting conservation assessments with behavioral data.

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。

Plan a comprehensive spectroscopic analysis campaign by defining the analytical question, assessing sample characteristics, selecting appropriate techniques using a decision matrix, planning sample preparation for each technique, sequencing analyses from non-destructive to destructive, and defining success criteria with a cross-validation strategy.

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。

Interpret a chromatogram from GC or HPLC analysis: verify system suitability parameters, identify peaks by retention time and spectral matching, perform accurate peak integration, calculate chromatographic figures of merit, and assess overall peak quality for reliable quantitation.

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。

Identify insects using body plan analysis, dichotomous keys to order, wing venation, mouthpart type, antennae form, leg and tarsal structure, and confidence levels. Covers the fundamental hexapod body plan verification, a simplified dichotomous key to major orders, wing venation and type analysis, mouthpart classification, antennae morphology, leg specialization and tarsal formula, and a structured confidence assessment framework. Use when you need to identify an unknown insect beyond preliminary order placement, are working through a specimen for taxonomic study, want to distinguish between similar orders or families, or need to assign a confidence level to a field identification.

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。

Investigate root causes and manage CAPAs (Corrective and Preventive Actions) for compliance deviations. Covers investigation method selection (5-Why, fishbone, fault tree), structured root cause analysis, corrective vs preventive action design, effectiveness verification, and trend analysis. Use when an audit finding requires a CAPA, when a deviation or incident occurs in a validated system, when a regulatory observation needs a formal response, when a data integrity anomaly requires investigation, or when recurring issues suggest a systemic root cause.

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。

Implement AI-powered anomaly detection for operational metrics using time series analysis (Isolation Forest, Prophet, LSTM), alert correlation, and root cause analysis. Reduce alert fatigue by intelligently identifying true anomalies in system metrics, logs, and traces. Use when operations teams are overwhelmed by alert volume, when detecting complex multi-metric anomalies beyond static thresholds, when seasonal patterns make thresholds ineffective, or when needing to predict issues proactively before they impact users.

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。

Systematically identify whether a GPU kernel is compute-bound, memory-bound, or latency-bound using roofline analysis, occupancy calculations, compute/load ratio per tile, and SASS instruction inspection. Produces a decision matrix for optimization strategy selection (cp.async, warp interleaving, tiling, double-buffering, or CuAssembler hand-tuning).

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。

Analyze the dynamics of diffusion processes using stochastic differential equations, Fokker-Planck equations, first-passage time distributions, and parameter sensitivity analysis. Use when deriving probability density evolution for a continuous-time diffusion process, computing mean first-passage times for bounded diffusion, analyzing how drift and diffusion parameters affect process behavior, or validating closed-form solutions against stochastic simulation.

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。

Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".

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 CodeQL and Semgrep static analysis with SARIF output for vulnerability detection, code quality assessment, and security compliance scanning across multiple languages.

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。

Automated brownfield codebase analysis with weighted keyword scoring, three-stream analysis, and design pattern recognition. Detects project type, frameworks, dependencies, architecture patterns, and generates comprehensive project profile.

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。

Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.

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。

Customer feedback analysis — sentiment detection, NPS/CSAT frameworks, feature request clustering, support ticket triage, churn signal detection, and feedback-to-roadmap translation

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。

Structured debug log analysis for Claude Code sessions — auto-discovers most recent log, runs reducer, extracts error patterns, correlates with full log, produces observability report. Fills 5 identified gaps: hook error body capture, agent identity, file path tracking, stall correlation, success visibility.

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。

Ultra-granular code analysis for deep architectural context building. Line-by-line and block-by-block analysis using First Principles, 5 Whys, 5 Hows methodology at micro scale. Builds mental models, tracks invariants and assumptions, and maps cross-function call flows for security audit preparation.

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。