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Responds to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing eradication procedures. Covers the full lifecycle from detection through containment, analysis, removal, and recovery. Activates for requests involving malware response, malware eradication, trojan removal, worm containment, malware triage, or infected endpoint remediation.
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Responds to phishing incidents by analyzing reported emails, extracting indicators, assessing credential compromise, quarantining malicious messages across the organization, and remediating affected accounts. Covers email header analysis, URL/attachment sandboxing, and mailbox-wide purge operations. Activates for requests involving phishing response, email incident, credential phishing, spear phishing investigation, or phishing remediation.
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。
Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel. Use when creating portable detection logic from threat intelligence, mapping rules to MITRE ATT&CK techniques, or converting community Sigma rules into platform-specific queries using sigmac or pySigma backends.
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 Microsoft Sentinel as a cloud-native SIEM and SOAR platform for centralized security operations. It details configuring data connectors for multi-cloud log ingestion, writing KQL detection queries, building automated response playbooks with Logic Apps, and leveraging the Sentinel data lake for petabyte-scale threat hunting across AWS, Azure, and GCP security telemetry.
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 the Malpedia platform and API to research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages.
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Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems.
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Create or update product-update / release-notes content for a given OpenMetadata/Collate patch version across getcollate, openmetadata-site, and docs-om. Sources getcollate's changelog from openmetadata-collate + OpenMetadata + ai-platform; openmetadata-site's from OpenMetadata only; docs-om reuses openmetadata-site's already-written content, reformatted into its Mintlify snippet structure. Filters to customer-facing changes only, runs each target's own doc-review checklist, verifies every link live, and requires explicit approval before any commit.
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。
Crawl and validate all internal and external links across an AEM Edge Delivery Services site. Uses the query index or sitemap to discover pages, extracts links from .plain.html renditions, checks HTTP status codes, and produces a prioritized report of broken, redirecting, and insecure links. Use when auditing link health before launch, after a migration, or as a periodic maintenance check.
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 images across AEM Edge Delivery Services pages for SEO and performance. Checks alt text quality, missing dimensions, lazy loading on LCP images, fetch priority, file naming, and decorative image handling. Generates a per-page report with specific fix instructions for alt text (in the source document) and performance attributes (in block code or scripts). Use when optimizing Core Web Vitals, improving image accessibility, or auditing image SEO.
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。
Compares the performance of two or more audience segments across key metrics side by side. Use this skill when someone wants to compare audiences, cohorts, or groups — for example, "how do mobile users compare to desktop users on conversion," "compare new vs. returning visitors," "show me the difference between these two segments," "compare these audiences on our KPIs," or "which segment performs better." Also trigger for "segment comparison," "audience comparison," or "cohort comparison."
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。
Compares the performance of two or more audience segments across key metrics side by side. Use this skill when someone wants to compare audiences or visitor groups — for example, "how do mobile visitors compare to desktop on conversion," "compare new vs. returning visitors," "show me the difference between these two segments," "compare these audiences on our KPIs," or "which segment performs better." Also trigger for "segment comparison" or "audience comparison."
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 and fix accessibility issues across the portfolio to ensure WCAG 2.1 AA compliance.
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。
Coordinate multi-step tasks across multiple skills for complex workflows.
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 beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across 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。
Compares old vs new prompts across test cases with diff summaries, stability metrics, breakage analysis, and fix suggestions. Use for "prompt testing", "A/B testing prompts", "prompt versioning", or "quality regression".
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Standardizes development environment setup across machines by generating tool version configs (Node, Python, Ruby), package manager configs (pnpm, Volta, asdf, mise), environment variable templates, and setup scripts with onboarding documentation. Use when users need to "setup dev environment", "standardize tooling", "configure version managers", or "create onboarding scripts".
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。
Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
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。
Installs and configures Prettier, ESLint, EditorConfig, and other code quality tools to enforce consistent code style across the team. Generates config files, npm scripts, editor settings recommendations, and CI integration suggestions. Use when users request "setup prettier", "add eslint", "configure code formatting", or "enforce code style".
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。
Unifies API response patterns across endpoints including pagination format, error structure, status codes, response envelopes, and versioning strategy. Provides contract documentation, shared TypeScript types, middleware utilities, and migration plan. Use when standardizing "API contracts", "response formats", "API conventions", or "API consistency".
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 Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.
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Use when sources must stay traceable across sessions and years, when each reference needs a passport recording where it was found, how it was verified, and where it is cited, or when a draft needs a cited-but-unverified sweep before submission.
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 a complete research workflow — its instructions, skills, data boundaries, and tool connections — must be assessed for portability across AI agents or environments, so each component is explicitly mapped before migration rather than assumed to transfer.
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 should be used when implementing features from a PRD spec, tracking implementation progress, or resuming work across sessions. Covers Dex task management for PRD story execution, daily workflows, and skill auto-loading.
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。
Advanced API exploitation methodology focused on business logic abuse and sophisticated attack patterns that bypass traditional security controls. Covers business logic bypass through API call chaining and workflow manipulation. Addresses GraphQL-specific attacks including batching for credential brute-force, query depth exploitation, and introspection abuse. Includes pagination exploitation for data exfiltration, webhook hijacking for SSRF and data interception, and resource exhaustion through algorithmic complexity attacks. Covers race conditions in API transactions using parallel request techniques. Provides comprehensive JWT manipulation including algorithm confusion, kid injection, jku/x5u abuse, and claim tampering. Details API key leakage detection across source repositories, client-side code, and error messages. Covers undocumented endpoint discovery through predictable naming, debug routes, and source map analysis. Tooling includes Arjun, ParamSpider, jwt_tool, and GraphQL Voyager. Designed for a...
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。