Integrates AI/LLM via Microsoft Agent Framework. Agents, workflows, tools, MCP servers, multi-agent orchestration.
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9천건 · 관련도순
Integrates AI/LLM via Microsoft Agent Framework. Agents, workflows, tools, MCP servers, multi-agent orchestration.
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Adds CI/CD to a .NET project. GitHub Actions vs Azure DevOps detection, workflow templates.
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Extend dev-software-engineer with .NET/C# backend specialization for Clean Architecture, CQRS, EF Core, and production-ready API practices. Use when tasks involve ASP.NET endpoints, handlers, services, dependency injection, MediatR, migrations, or backend performance/resilience and should follow the base implementation workflow.
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Use for non-trivial feature, behavior, workflow, or architecture work before execution planning. Create or update a versioned spec under planning/specs/active with design intent, alternatives, risks, acceptance criteria, and planning readiness.
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Build and maintain CI/CD pipelines, containerization, Kubernetes manifests, and quality gates for this repository. Use when the user asks for Docker, Kubernetes, GitHub Actions/Azure DevOps pipelines, deployment, reliability, or static analysis workflows.
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Build and maintain CI/CD pipelines, containerization, Kubernetes manifests, and quality gates. Use when tasks involve Docker, Kubernetes, GitHub Actions/Azure DevOps pipelines, deployment, reliability, or static analysis workflows.
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Git commit and pull request conventions. USE FOR: writing commit messages; checking Conventional Commits and gitmoji; branch naming; rebase workflow on develop; PR titles and target branch. PRIORITY: this skill overrides other rules when creating commits/PRs. DO NOT USE FOR: code implementation (use code-implementation skill); testing (use test-writing skill); general documentation (use documentation skill).
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Configure GSD workflow toggles and model profile
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Automatically advance to the next logical step in the GSD workflow
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Post-mortem investigation for failed GSD workflows — analyzes git history, artifacts, and state to diagnose what went wrong
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Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.
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Evaluates and selects Threat Intelligence Platform (TIP) products based on organizational requirements including feed integration capability, STIX/TAXII support, workflow automation, analyst interface, and total cost of ownership. Use when conducting a TIP procurement, migrating between TIP solutions, or assessing whether the current TIP meets program maturity requirements. Activates for requests involving ThreatConnect, MISP, OpenCTI, Anomali, EclecticIQ, or TIP procurement decisions.
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This skill teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous threat detection across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity levels, and building automated response workflows using EventBridge and Lambda.
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Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.
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Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.
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Build a vulnerability exception and risk acceptance tracking system with approval workflows, compensating controls documentation, and expiration management.
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Builds comprehensive identity governance and lifecycle management processes including joiner-mover-leaver automation, role mining, access request workflows, periodic recertification, and orphaned account remediation using IGA platforms. Activates for requests involving identity lifecycle management, JML processes, role-based access provisioning, or identity governance program design.
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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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Orchestrate complete lifecycle work for the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM as a Cloud Service, from design and implementation through validation, release readiness, and incident troubleshooting.
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Orchestrates end-to-end replication workflows spanning multiple concerns: new environment setup, production incident response, and performance optimization for AEM 6.5 LTS.
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Reconcile a converted/built web page against its source prototype with two complementary probes — a PIXEL/layout diff (stretched images, dropped wraps, blank renders, colour flips) and a STRUCTURAL content+typography diff (dropped/mis-slotted headings, eyebrows, CTAs; rendered-face font forks). Stack-agnostic via profiles (eds | generic). Use after converting a prototype to EDS/AEM (the stardust:deploy Step 10), or for any prototype↔build fidelity check; invocable as stardust:diff and from workflows.
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Optimize performance of the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration for AEMaaCS cloud workflows only, with cloud-specific baseline and runtime verification.
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Provide advisory guidance for the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEMaaCS cloud workflows only, with public-doc citations and cloud-specific MCP verification plans. Use for conceptual questions such as `statfileslevel`, filter rules, URL decomposition, cache invalidation behavior, rewrite behavior, and security headers.
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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.
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