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Found 10,562 Skills
Real-time quotes, K-line charts, order book, trade ticks, intraday capital flow, market sentiment temperature, trading session schedule, security lists, exchange rates, and IPO calendar for HK/US/A-share/SG via Longbridge. Also covers ADR premium and FX carry frameworks. Triggers: "股价", "行情", "K线", "走势", "盘口", "资金流", "市场温度", "汇率", "IPO", "打新", "隔夜股", "ADR溢价", "外汇套息", "K線", "盤口", "資金流", "市場溫度", "匯率", "ADR溢價", "外匯套息", "现在多少钱", "多少钱", "stock price", "quote", "kline", "chart", "depth", "orderbook", "capital flow", "market sentiment", "exchange rate", "IPO calendar", "security list", "ADR premium", "fx carry", "market open", "trading hours", "开市", "溢价", "NVDA.US", "700.HK", "600519.SH", "股價", "走勢", "開盤", "今天開市"
Build, modify, debug, and deploy agents with Agentforce Agent Script. TRIGGER when: user creates, modifies, or asks about .agent files or aiAuthoringBundle metadata; changes agent behavior, responses, or conversation logic; designs agent actions, tools, subagents, or flow control; writes or reviews an Agent Spec; previews, debugs, deploys, publishes, or tests agents; uses Agent Script CLI commands (sf agent generate/preview/publish/test). DO NOT TRIGGER when: Apex development, Flow building, Prompt Template authoring, Experience Cloud configuration, or general Salesforce CLI tasks unrelated to Agent Script.
MUST activate when a uiBundles/*/src/ project does ANY Salesforce record operation — reading, creating, updating, deleting, or caching/refreshing query results. Triggers: code importing @salesforce/platform-sdk, calls to sdk.graphql.query / sdk.graphql.mutate / sdk.fetch, *.graphql files, stale data needing a force-refresh, or wiring up a UI bundle's data layer to read, write, or refresh Salesforce records. The default for new read/write work is the Read/Write workflow with the current @salesforce/platform-sdk API; only follow the migration path when EXISTING code already uses the old @salesforce/sdk-data callable form. Not for building app shell/UI, styling, file upload, or auth/search scaffolding — use the other ui-bundle-* skills. DO NOT TRIGGER when: OAuth setup, schema changes, Bulk/Tooling/Metadata API, or declarative automation.
Runs SQL queries on CloudWatch Logs data exported as Apache Iceberg tables in S3 Tables. Covers VPC Flow Logs, WAF logs, CloudFront access logs, Route 53 resolver logs, Network Firewall logs, EKS audit logs, Verified Access logs, SES logs, VPC Lattice logs, Step Functions logs, NLB access logs, and 20+ other AWS vended data sources. Applies when analyzing network traffic, investigating security incidents, querying exported logs with SQL, enabling S3 Tables integration, configuring log export, correlating logs with other data, or running Athena queries on the aws-cloudwatch table bucket. Trigger phrases: query logs with SQL, analyze logs in Athena, SQL on VPC flow logs, investigate network traffic, run SQL on exported logs, enable S3 Tables for CloudWatch, correlate logs, historical log analysis, set up log querying.
Automates the end-to-end detection engineering workflow in Google SecOps using MCP tools. Use when fetching threat intelligence from blogs, generating Threat Detection Opportunities (TDOs), simulating attacker behavior with synthetic UDM events, evaluating rule coverage, and generating new YARA-L 2.0 rules to close coverage gaps. Don't use when asked to perform threat hunting actions, and SOC investigative actions.
Create, read, list, search, and manage Tencent Docs (腾讯文档) — online documents, sheets, slides, mind maps, flowcharts, smart tables, and forms — via the Tencent Docs Open API. Use when the user mentions 腾讯文档 / Tencent Docs / docs.qq.com, a docs.qq.com link, or wants to create / read / organize a doc, sheet, slide, mind map, or flowchart in their Tencent Docs space.
Create a SageMaker endpoint (real-time or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever about to create a SageMaker endpoint, write deployment code that calls `create_endpoint`, or finalize a deployment after the image URI and IAM role are known. Provides deploy.py for real-time endpoints and deploy_async.py for async endpoints (with genuine scale-to-zero support). This is the last step in the SageMaker deployment workflow. Never generate a bare `create_endpoint` call without these defaults — endpoints without autoscaling or alarms are demos, not deployments.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
Complete SEO skill for technical audits (Core Web Vitals, site speed, crawlability/indexation, robots/sitemaps/canonicals, structured data, mobile, security, internal linking), SEO marketing strategy (keyword research, content planning, competitive analysis, E-E-A-T), operational workflows (cross-team collaboration, OKRs), link building, local SEO, international SEO (hreflang), and multi-platform SEO (Google, YouTube, Reddit, social). Updated for January 2026.
Skill for handling PR code reviews. Use when triggered by a PR review comment, review request, or when asked to review code changes. Provides workflow for reading review comments, understanding feedback, and iterating on changes.
Security-focused code review checklist and automated scanning patterns. Use when reviewing pull requests for security issues, auditing authentication/authorization code, checking for OWASP Top 10 vulnerabilities, or validating input sanitization. Covers SQL injection prevention, XSS protection, CSRF tokens, authentication flow review, secrets detection, dependency vulnerability scanning, and secure coding patterns for Python (FastAPI) and React. Does NOT cover deployment security (use docker-best-practices) or incident handling (use incident-response).
Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.