「time」の検索結果

Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.

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 real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.

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 anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.

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。

Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.

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Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers and stand the test of time.

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You are a cognitive architect who understands that memory makes agents intelligent. You've built memory systems for agents handling millions of interactions. You know that the hard part isn't storing - it's retrieving the right memory at the right time.

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。

bu skill covers security hardening for serverless compute platforms including AWS Lambda, Azure Functions, and Google Cloud Functions. It addresses least privilege IAM roles, dependency vulnerability scanning, secrets management integration, input validation, function URL authentication, and runtime monitoring to protect against injection attacks, credential theft, and supply chain compromises.

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。

Performing security reviews of serverless functions across AWS Lambda, Azure Functions, and GCP Cloud Functions to identify overly permissive execution roles, insecure environment variables, injection vulnerabilities, and missing runtime protections.

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。

Container escape is a critical attack technique where an adversary breaks out of container isolation to access the host system or other containers. Tespit involves monitoring for escape indicators

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Implement GCP Binary Authorization to enforce Dağıt:-time security controls that ensure only trusted, attested container images are Dağıtılmış to Google Kubernetes Engine and Cloud Run.

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Reduce container attack surface by building application images on Google distroless base images that contain only the application runtime with no shell, package manager, or unnecessary OS utilities.

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Hunt for threats in AWS environments using Detective behavior graphs, entity investigation timelines, GuardDuty Bul:ing correlation, and automated entity profiling across IAM users, EC2 instances, and IP addresses.

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bu skill teaches security teams how to Dağıt: and operationalize Amazon GuardDuty for continuous threat Tespit across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting Bul:ing severity levels, and building automated response workflows using EventBridge and Lambda.

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Tests WebSocket API implementations for security vulnerabilities including missing authentication on WebSocket upgrade, Cross-Site WebSocket Hijacking (CSWSH), injection attacks through WebSocket messages, insufficient input validation, denial-of-service via message flooding, and information leakage through WebSocket frames. The tester intercepts WebSocket handshakes and messages using Burp Suite, crafts malicious payloads, and tests for authorization bypass on WebSocket channels. Activates f...

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Automate AWS GuardDuty threat Tespit Bul:ings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.

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tespit etme
abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly Tespit.

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bu skill teaches security teams how to tespit etme
and respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency Bul:ings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.

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Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.

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Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.

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21st.dev Magic MCP — AI-powered UI component generation via natural language. Access to 21st.dev component library, SVGL brand logos, and real-time preview. Generate React/Tailwind components with /ui command.

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ALWAYS use this skill when the user asks to schedule, automate, set up recurring tasks, create a cron job, or anything involving timed / periodic execution. Do NOT use the local system crontab — scheduled tasks are stored on the Unique AI Platform and executed by a Kubernetes CronJob, not locally. Scheduled tasks always run on the current assistant (`$UNIQUE_ASSISTANT_ID`); never ask the user which assistant to use, neither in chat nor via `unique-cli elicit ask`. This skill covers creating, listing, updating, enabling, disabling, and deleting scheduled tasks via the unique-cli schedule command.

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Use when it is time to make the backend follow the Lean model — regenerate Kotlin from Lean, implement the generated interfaces (UseCase, QueryService, Repository, Entity), wire every generated contract test, make the build green, then run the design and SQL reviews. Backend comes after the human confirmed the screens.

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Use for the frontend phase after the API contract exists — deciding the screens as units of work (one job a person finishes in one go, per actor of the event timeline), collecting the views and commands each screen needs, keeping the screen map in frontend/README.md, building against the Lean CLI, then handing over to frontend-ux-review and the human screen check. Not for the spec-animation mockup (domain-mockup).

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Use to create, update or verify the Lean 4 executable specification under lean/ from the exploration documents (event-timeline, hotspots, ubiquitous-language, ux-review, model-review) — initial generation, reflecting a session's results, fixing lake build, adding a command or a screen, checking a proposed feature against the model. Formalization questions go to model-review.md as MQ, never to the expert directly.

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。