666 件 ・ 関連度順
概要と使いどころ
Builds automated threat intelligence feed integration pipelines connecting STIX/TAXII feeds, open-source threat intel, and commercial TI platforms into SIEM and security tools for real-time IOC matching and alerting. Use when SOC teams need to operationalize threat intelligence by automating feed ingestion, normalization, scoring, and distribution to detection systems.
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Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.
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Designs and documents structured incident response playbooks that define step-by-step procedures for specific incident types aligned with NIST SP 800-61r3 and SANS PICERL frameworks. Covers playbook structure, decision trees, escalation criteria, RACI matrices, and integration with SOAR platforms. Activates for requests involving IR playbook creation, incident response procedure documentation, response runbook development, or SOAR playbook design.
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Uses the Linux Audit framework (auditd) with ausearch and aureport utilities to detect intrusion attempts, unauthorized access, privilege escalation, and suspicious system activity. Covers audit rule configuration, log querying, timeline reconstruction, and integration with SIEM platforms. Activates for requests involving auditd analysis, Linux audit log investigation, ausearch queries, aureport summaries, or host-based intrusion detection on Linux.
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 DNS query logs to detect data exfiltration via DNS tunneling, DGA domain communication, and covert C2 channels using entropy analysis, query volume anomalies, and subdomain length detection in SIEM platforms. Use when SOC teams need to identify DNS-based threats that bypass traditional network security controls.
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 a BMad skill into a downloadable web bundle (Gemini Gem + ChatGPT Custom GPT) with a persona, install instructions, and knowledge files. Use when a user wants to publish a skill to consumer LLM platforms (Gemini, ChatGPT).
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- Enumerate a username across hundreds of platforms with sherlock, maigret and WhatsMyName, then correlate and confirm which accounts genuinely belong to the same person.
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- Build a sourced, corroborated profile of a named individual from public records, social platforms, professional networks, court and property filings, licensing boards, patents, papers and obituaries — anchoring the name to a… Use when asked to find, identify, background-check or profile a person, verify someone's claimed employment or credentials, or locate a missing or hard-to-reach individual
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。
Senior engineer CLI expertise for AI agents — workflows, safety guardrails, gotchas, and anti-patterns across cloud, IaC, containers, databases, dev tools, and platforms
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。
Create platform-optimized social media content — captions, hashtags, headlines, calls-to-action. Covers tone-of-voice, character limits, hook writing, A/B testing variants, and content repurposing across platforms. Use when writing captions, generating hashtags, crafting hooks, creating A/B test variants, adapting content per platform, or setting up an editorial voice.
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。
Create and process videos using AI generation (Runway, Pika, Replicate, Sora, Veo) and FFmpeg processing. MCP bridge provides frame extraction (extract_video_frames); the Design Stack media worker handles full FFmpeg processing (resize, trim, compress, GIF, format conversion). Covers social-media-optimized video output. Use when generating AI videos, extracting frames/thumbnails, transcoding videos, creating GIFs from clips, or preparing video for social platforms.
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。
Scrape leads from multiple platforms using Apify Actors.
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。
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
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-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your task.
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。
Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for
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 when the user asks to "track our share of voice", "what share of the conversation do we own vs competitors", or "trend our SOV this quarter"; computes SOV% = brand mentions ÷ (brand + competitor panel mentions) per platform per period on a LOCKED competitor panel — a panel switch invalidates the trend (restart the series and log the break; the ECHO O3 rule) — plus a sentiment-weighted SOV variant (sentiment labeled Estimated unless human-coded) and a Wikipedia-pageviews attention-share alternative; built from keyless listening connectors, gdelt.py news echo, and user exports — public counts only, closed platforms are never scraped. Not for backlink or offsite SEO signals — use offsite-signal-analyzer. 声量份额/竞品声量对比/提及份额/注意力份额
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 when the user asks to "build the norm card for this platform", "what are the char limits and visible-fold cutoffs here", "is the LinkedIn link-in-first-comment thing documented or folklore", or "which of our platform cards are stale"; maintains the dated, versioned per-platform norm cards in the references/platforms/ pack — char limits, visible-fold cutoffs, hashtag norms, format/aspect specs, link and first-comment placement, disclosure-label mechanics, algorithm emphases (e.g. 小红书 search+saves weighting) — every row labeled platform-documented (official doc, Measured) or Estimated-folklore (named source) with last-verified and review-by dates, and any card past its review date flagged stale rather than trusted. Extends the single pack in place; never forks a second one. Not for picking which channels to run — use channel-portfolio-planner. 平台规范卡/字符限制/折叠线/话题标签/算法侧重/过期标记
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 when the user asks to "build audience segments from my customer list", "make value-based / lookalike seed lists", "set up exclusion / suppression segments", or "map audiences to funnel stages across platforms"; turns the user's OWN customer/CRM/GA4 export into seed audiences, value-based lookalike SEED lists, exclusion/suppression segments, and a cross-platform funnel-stage targeting map, informing the ROAS A (Audience) dimension. Not for building account structure or match types — use campaign-architect; not for organic SERP intent — use keyword-research. 付费广告受众分群/种子人群/排除人群/相似人群种子
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 and optimize paid media across search, social and other platforms, including account structure, targeting, bidding, measurement, budget and creative testing.
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 paid-ad copy, images, video, hooks, concepts, format coverage, platform-native fit, message match, creative fatigue, accessibility, and policy across supported platforms. Use for creative audit, ad creative, creative fatigue, creative diversity, ad copy review, video review, image review, or production priorities.
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 and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or investment tradeoffs.
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。
Monitor paid-ad account pacing, delivery, performance, creative fatigue, tracking, policy, and data quality across supported platforms. Use for daily or weekly checks, anomaly review, budget pacing, post-launch verification, or campaign monitoring.
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Research competitor paid-ad presence, messaging, creative, formats, landing pages, keyword and auction signals, transparent ad libraries, and strategic gaps across supported platforms. Use for competitor ads, ad libraries, ad spy, competitive PPC analysis, competitor creative, Google Ads Transparency, Meta Ad Library, or paid-media competitor research.
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。
Complete Flutter SDK installation, IDE configuration, and troubleshooting guide for Linux, macOS, and Windows. Use for installing Flutter SDK from scratch, configuring PATH environment variables across platforms, setting up VS Code/Android Studio/IntelliJ IDEA with Flutter plugins, resolving 'flutter command not found' errors, fixing flutter doctor warnings and errors, troubleshooting Android SDK/NDK installation issues, configuring Xcode and CocoaPods on macOS, installing Visual Studio C++ build tools on Windows, resolving PATH conflicts and SDK path issues, fixing network/proxy setup problems, debugging IDE plugin activation, configuring emulators and simulators, handling platform-specific build errors, resolving dependency conflicts, fixing certificate and signing issues, troubleshooting hot reload failures, and verifying successful installation with flutter doctor diagnostics.
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。