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概要と使いどころ
Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.
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Analyze text and images for harmful content using Azure AI Content Safety (@azure-rest/ai-content-safety). Use when moderating user-generated content, detecting hate speech, violence, sexual content, or self-harm, or managing custom blocklists.
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。
Reconstruct workflow behind a past coding-agent artifact using local ax sessions/commits/skills/tool traces. Use when asked how X was built.
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 Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
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。
Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, confidence scoring, and command validation.
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。
Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.
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。
Agile product ownership for backlog management and sprint execution. Covers user story writing, acceptance criteria, sprint planning, and velocity tracking. Use for writing user stories, creating acceptance criteria, planning sprints, estimating story points, breaking down epics, or prioritizing ...
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。
Audit a live page for accessibility issues, locate each WCAG violation precisely, and return a selector-grounded fix worklist without editing.
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。
Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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。
Verify Stripe subscription billing cycles using a test clock. Use when you need to simulate time passing to trigger subscription renewals, recurring invoices, or to confirm that the next billing date generates the expected charge in Stripe test 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。
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.
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 monitors ransomware canary files across critical directories using Python's watchdog library for real-time filesystem event detection. Places strategically named decoy files that mimic high-value targets (financial records, credentials, database exports) in locations ransomware typically enumerates first. Monitors for any read, modify, rename, or delete operations on canary files and triggers immediate alerts via email, Slack webhook, or syslog when interaction is detected, providing early warning before full encryption begins.
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 compromised O365 and Google Workspace email accounts by analyzing inbox rule creation, suspicious sign-in locations, mail forwarding rules, and unusual API access patterns via Microsoft Graph and audit logs.
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。
Correlates security events in IBM QRadar SIEM using AQL (Ariel Query Language), custom rules, building blocks, and offense management to detect multi-stage attacks across network, endpoint, and application log sources. Use when SOC analysts need to investigate QRadar offenses, build correlation rules, or tune detection logic for reducing false positives.
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。
Use Intel CHIPSEC to assess platform firmware configuration, SPI flash write protection, BIOS lock, SMM/SMRR, and Secure Boot variable state, dump SPI flash, and triage UEFI variables for firmware-level threats.
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。
Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems.
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。
Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.
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。
Perform static and symbolic analysis of Solidity smart contracts using Slither and Mythril to detect reentrancy, integer overflow, access control, and other vulnerability classes before deployment to Ethereum mainnet.
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 and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.
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。
Convert LaTeX papers between journal/conference templates for journal resubmission or template switching (e.g., Springer → MDPI, IEEE → Nature, IPOL → CVPR) through a privacy-preserving anonymized workflow. Use when the user provides a LaTeX .tex/project plus a target template directory or .tex file. Assume the input is not anonymized unless the user explicitly says it is already anonymized. Preserve privacy sentinels exactly; never open mapping.private.json except as a local script argument.
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 cyclist's training week as a standalone coaching package with integrated workout building. Use whenever the athlete asks to plan a week or the upcoming week ("plan my week", "build my training week", "week schema", "plan a week workout schedule", or any localized equivalent), or states a goal for the week. The flow reads a per-athlete config, pulls recent Strava data, classifies rider type from the athlete's own power curve, then produces one weekly markdown plan and structured bike workouts (ZWO for Zwift) per structured bike session without relying on another skill. Works for any cyclist, not one fixed person.
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。
Pull remote changes and reconcile with local work, checking for soft conflicts
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。
Update npm/yarn/pnpm dependencies using manifest-first, lockfile-aware workflows. Prefer declared version bumps over resolution overrides. Use when updating, upgrading, or patching dependencies; fixing transitive dependency versions; addressing npm audit or CVE findings; or removing stale overrides.
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。