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Found 118 Skills
Turns an approved cut into the finished video in a creator's measured style. Takes cut.mp4 from the cut skill plus a style.json (from start or creator-teardown), plans captions and zooms to match the creator, adds visuals timed to the spoken word (the user's own images, real screenshots, posts and logos of what is named, the line marked on the real page; no type cards, stock icons or emoji), shows the stills on the review page for approval, then renders 9:16 or 16:9 with Remotion on the laptop, Modal, GitHub Actions or the user's AWS Lambda, and can export the edit to Final Cut, Premiere, Resolve or CapCut. Use when a cut already exists and the user says "style it", "now add the style", "add captions and zooms", "add my images to the video", "render the edit", "change the captions", "export to Final Cut" or "send it to Premiere". Not for a raw take or a first request to edit a video like a creator (that is start), not for cutting mistakes out (cut), and not for measuring a creator (creator-teardown).
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.
Use when you need to refactor Java code to adopt modern Java features (Java 8+) — including migrating anonymous classes to lambdas, replacing Iterator loops with Stream API, adopting Optional for null safety, switching from legacy Date/Calendar to java.time, using collection factory methods, applying text blocks, var inference, or leveraging Java 25 features like flexible constructor bodies and module import declarations. Part of the skills-for-java project
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Provides authoritative guidance on Amazon Neptune Database and Neptune Analytics for graph, knowledge-graph, and relationship-heavy workloads — fraud detection / fraud rings, agentic memory / chatbot context across sessions, recommendations, identity resolution, Gremlin / openCypher / SPARQL queries, supernode / slow traversal, Neo4j to Neptune migration / APOC compatibility, Neptune Database vs Analytics engine selection, PageRank / community detection, GraphRAG, and connectivity from Lambda / EC2 / applications. Creates and modifies Neptune Database clusters/instances and Neptune Analytics graphs on explicit user confirmation; blocks destructive operations (delete, reset-graph, failover, major upgrade) and redirects to change-control.
Use this skill to fix scroll jank, lost item state, and broken animateItem() animations in LazyColumn, LazyRow, LazyVerticalGrid, and LazyHorizontalGrid. Covers stable item keys, contentType for mixed-type feeds, Modifier.animateItem() requirements, hoisting modifier chains and painters out of the items lambda, and validating item composable stability. Use when the developer mentions LazyColumn jank, dropped frames while scrolling, items losing scroll state on insert/remove/reorder, mixed feeds of cards/headers/ads feeling sluggish, animateItem() not animating, RecyclerView view-type analog, key parameter, or contentType parameter. The prefetch-window tuning lives in a sibling skill.
Entry point for AI-agent work on AWS: pick a runtime, plan a migration for existing workloads, and build an executable POC — one phased flow. Triggers on: which runtime for my agent, AgentCore vs ECS vs EKS vs Lambda, AgentCore vs Lambda MicroVMs, deploy an AI agent on AWS, agent architecture on AWS, I have an agent idea what do I build, move/migrate my agents to AWS, agent migration plan, add AgentCore services (memory, gateway, identity, policy, observability) to an agent already on AWS, Temporal on AWS (migrate/run Temporal workers on AWS, a service orchestrated by Temporal, Temporal Cloud vs self-hosted). Temporal Workflow code is never rewritten into Step Functions. Requires at least one agentic component — a purely non-agent system (plain services, batch jobs, HTTP endpoints, non-agent Temporal Activities) is out of scope, redirected to gcp-to-aws / heroku-to-aws / llm-to-bedrock. Not for: compute/data migration with no AI agent; pure LLM SDK rewrite (use llm-to-bedrock); per-model pricing.
Hunt cloud / infrastructure misconfigurations. AWS: public S3 buckets (s3:GetObject anonymous), permissive bucket policies (PutObjectAcl public-write), exposed CloudFront origin, public Lambda function URL, public RDS snapshot, IAM credentials in JS bundles, AWS metadata accessible via SSRF. GCP: public GCS buckets, exposed Cloud Run services, leaked service account JSON. Azure: public blob containers, exposed Function App. (Kubernetes/Docker exposure is owned by hunt-k8s; CI/CD pipeline attacks by hunt-cicd; post-credential IAM escalation by cloud-iam-deep.) Detection: targeted dorking, certificate transparency, JS bundle secret extraction, port scan for known service ports. Validate: actual data read / write / RCE. Use when hunting cloud-native storage and compute misconfig (S3/GCS/Blob, IMDS-via-SSRF, serverless, public managed services).
You are an expert in Hono, the ultrafast web framework for the edge. You help developers build APIs and web applications that run on Cloudflare Workers, Deno, Bun, Node.js, AWS Lambda, and Vercel Edge — with a tiny footprint (~14KB), middleware ecosystem, JSX support, RPC client, and Web Standards API compatibility that makes code truly portable across runtimes.
Deploy self-hosted OAuth2 and OIDC servers with OpenAuth, createSubjects schemas, prebuilt PasswordUI/CodeUI, and cross-framework client verification. Use when building universal auth for Cloudflare Workers, Node.js, Bun, and AWS Lambda with @openauthjs/openauth, social logins, and secure session rotation.
Investigate cloud-provider (CSP) service issues — AWS today (the reasoning applies to any AWS service; schema and failure signatures are deepest for RDS, Lambda, SQS, ALB, EC2), and in future GCP and Azure — using OTel-schema cloud metrics in Elastic. Use when diagnosing cloud-resource problems, whether alert-triggered or ad hoc: database connection/CPU/memory pressure, function error rates and throttling, queue backlog and consumer lag, load-balancer 5xx, instance saturation. Correlates the resource under investigation against its own baseline, classifies the failure mode, and rules out co-occurring but unrelated conditions.
MyBatis-Plus 增强 ORM 技能。覆盖 LambdaQueryWrapper vs QueryWrapper选择(始终Lambda)、分页插件(PaginationInnerInterceptor)配置、乐观锁(@Version + OptimisticLockerInnerInterceptor)、逻辑删除(@TableLogic 全局/局部配置)、自动填充(@TableField fill + MetaObjectHandler)、ActiveRecord vs Mapper模式选择、防全表更新(BlockAttackInnerInterceptor)、通用PageQuery抽取。 当用户使用 MyBatis-Plus 进行数据库操作、配置分页乐观锁、选择查询方式时使用。 与 mybatis 技能互补：mybatis 侧重XML/ResultMap/SQL写法，mybatis-plus 侧重增强功能。