5,121 件 ・ 関連度順
Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing 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。
Scan the project for refactoring opportunities, then fix them. No behavior/visual changes.
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。
Check docs/ai/ spec files and ADRs for inconsistencies with the codebase, then fix all discrepancies.
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。
Diagnose and fix common AEM 6.5 LTS replication issues including blocked queues, connectivity failures, and content distribution problems
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。
Analyze and improve the internal link structure of an AEM Edge Delivery Services site. Builds a link graph from the query index and page content, identifies orphan pages, hub pages, and content silos, and generates specific linking recommendations with suggested anchor text and placement. Use when improving site navigation, fixing orphan pages, strengthening topical authority, or auditing link equity distribution.
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 optimize headings across AEM Edge Delivery Services pages for search intent, hierarchy, and consistency. Extracts all headings (H1-H6), evaluates uniqueness, keyword alignment, specificity, and structural correctness, then generates optimized heading suggestions per page. Use when improving on-page SEO, fixing heading hierarchy issues, or standardizing heading patterns across a site.
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。
Migrates legacy AEM (6.x, AMS, on-prem) to AEM as a Cloud Service using BPA CSV or cache, CAM/MCP target discovery, and a one-pattern-per-session workflow. Use for BPA/CAM findings, Cloud Service blockers, or fixes for scheduler, ResourceChangeListener, replication, EventListener, OSGi EventHandler, DAM AssetManager, HTL data-sly-test lint. OSGi configs → Cloud Manager — scan ui.config, .cfg.json, secrets, $[secret:]/$[env:] — agent follows references/osgi-cfg-json-cloud-manager.md when prompted. After BPA/CAM discovery, migration hands off each (pattern, file) pair to the code-assessment skill — code-assessment owns the five pattern guides (scheduler/, resource-change-listener/, replication/, event-migration/, asset-manager/) and the shared references for SCR→DS, ResourceResolver/SLF4J, HTL lint, and prerequisites.
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。
[BETA] AEM Cloud Service expert skill — migrate javax.inject.@Inject fields in Sling Model (@Model) classes to injector-specific annotations (@ValueMapValue / @OSGiService / @SlingObject). Self-discoverable (scan for @Model classes with field-level @Inject); the replacement is chosen deterministically from each field's declared type. Use for "fix @Inject in HeroModel.java", "modernize my Sling Models", or when scanning an AEM project for @Inject misuse. Detailed decision table, companion-annotation handling, import management, and file-level skip policy are in recipe.md. This skill is in beta. Verify all outputs before applying them to production projects.
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 an AEM Edge Delivery Services page for content quality, SEO, accessibility, performance, and EDS best practices. Produces a prioritized fix list with specific remediation steps. Use when reviewing page quality, preparing for launch, or optimizing existing content.
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。
Apply a Content Driven Development process to AEM Edge Delivery Services development. Use for ALL code changes - new blocks, block modifications, CSS styling, bug fixes, core functionality (scripts.js, styles, etc.), or any JavaScript/CSS work that needs 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 and update metadata across multiple AEM Edge Delivery Services pages. Scans pages via the query index, identifies missing or inconsistent metadata (titles, descriptions, og tags, robots), and generates a corrected bulk metadata spreadsheet. Use when standardizing metadata across a site, preparing for launch, or fixing SEO issues at scale.
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。
AI regression scouting routing. Use when agents, prompts, skills, model/tool routing, harness fixtures, or generated-output expectations change and need regression scenarios; do not use for ordinary product-code regressions.
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。
Diagnose user-reported AILI/ROSE harness or workflow behavior problems without editing files; use when the user says a command, skill trigger, subagent packet, memory flow, installer, docs, or agent prompt behavior is wrong and wants to know where the issue lives and how to fix it. Do not use for normal product-code bugs; return any approved modification need to ROSE.
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, edit, fix, or explain Mermaid diagrams for relationships, decision branches, interactions, lifecycles, and data models; also use when the parent selects a diagram to materially clarify an explanation. Do not trigger for simple status, one fact, short lists, quantitative charts, or marketing slides.
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。
Code-review quality gate and test-enhancement rubric. Use when ROSE needs sharper review output contracts, severity and risk prioritization, evidence anchors, negative review cases, fixture or golden-output drift guidance, or a Chinese review report profile; do not use as a duplicate code-review agent or final PASS authority.
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。
Conduct one bounded evidence-grounded code review when the user explicitly requests review or ROSE names a concrete unresolved correctness/quality risk; do not trigger automatically after implementation, before every merge, for every bug fix/refactor, or as a completion gate.
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。
Automatically categorizes test failures, suggests responsible owners, and provides common fix checklists. Generates actionable test reports with failure analysis. Use for "test reporting", "failure triage", "test analysis", or "test automation".
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。
How to write modern Swift well — modeling with value types, Swift 6 data-race safety and approachable concurrency (@concurrent, main-actor-by-default, actors, task groups), protocols and generics (some vs any), API design, performance and ARC, Swift Testing, macros, and the modern language features agents don't know about yet. Use when writing, reviewing, or migrating Swift, or when a concurrency error, a hang, a data race, a retain cycle, or a performance problem needs fixing.
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。
Audits database schemas for naming conventions, type consistency, nullability patterns, and missing constraints. Provides violations report with recommended fixes. Use for "schema validation", "database linting", "schema standards", or "consistency checks".
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。
UI/UX design intelligence for web, mobile, and desktop. This skill should be used when designing, building, reviewing, or fixing interfaces, including pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, and stack-specific UI implementation. Searchable local data: 79 searchable styles (50 active), 192 product palettes and reasoning profiles, 74 font pairings, 119 UX guidelines, 105 icons, 17 GSAP presets, 25 chart types, and 22 stacks.
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。
Creates factories and builders for generating consistent, composable test data with realistic values and relationship handling. Use for "test factories", "test data builders", "fixture factories", or "test data generation".
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".
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。