「behavioral」の検索結果

Apply behavioral science and mental models to marketing decisions, prioritized using a psychological leverage and feasibility scoring system.

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。

Behavioral UX specialist applying choice architecture, friction audits, and commitment design to guide users toward intended actions without coercion. Use when optimizing conversion flows, onboarding, or checkout UX.

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。

Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review, regression review, security review, or wants high-signal issues plus a prioritized fix path without editing files.

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。

Behavioral guardrails for implementation work. Reduces common LLM coding mistakes: overcomplication, silent assumption-picking, scope drift, and unverifiable success criteria. Load on Builder and software-engineer-mode.

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。

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

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。

Mandatory skills, conventions, and behavioral rules for Avalonia UI development using the Zafiro toolkit.

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。

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test 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。

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

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。

Mandatory skills, conventions, and behavioral rules for Avalonia UI development using the Zafiro toolkit.

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。

tespit etme
unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.

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 User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.

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。

Detects and analyzes process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis to identify injection artifacts. Activates for requests involving process injection detection, code injection analysis, hollowed process investigation, or in-memory threat detection.

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。

Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app 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。

Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs. Uses pandas for behavioral analytics and statistical baselines. Use when investigating insider threats or building user behavior analytics for data loss prevention.

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 insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.

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 unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.

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。

Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs. Activates for requests involving authentication anomaly detection, login behavior analysis, UEBA implementation, or suspicious sign-in 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。

This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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。

Deploys and configures CrowdStrike Falcon EDR agents across enterprise endpoints to enable real-time threat detection, behavioral analysis, and automated response. Use when onboarding endpoints to EDR coverage, configuring detection policies, or integrating Falcon telemetry with SIEM platforms. Activates for requests involving CrowdStrike deployment, Falcon sensor installation, EDR policy configuration, or endpoint detection and response.

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 collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.

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。

Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.

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。

Completes the online SBTI personality test at sbti.fancc.de5.net, answers all single-choice questions using the model's default personality and stable behavioral tendencies, submits the test, and returns the final type, match percentage, result description, and fifteen-dimension scores. Use when the user asks to take the SBTI test, run the SBTI quiz, get an SBTI result, or complete that personality test website for them.

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。

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

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。

Mandatory skills, conventions, and behavioral rules for Avalonia UI development using the Zafiro toolkit.

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。