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Found 2,407 Skills
Claude CLI sub-agent system for persona-based analysis. Use when piping large contexts to Anthropic models for security audits, architecture reviews, QA analysis, or any specialized analysis requiring a fresh model context.
Execute token swaps and manage on-chain transactions: list supported swap chains, browse available swap tokens, get swap quotes with price/slippage/route info, build signable swap transactions, estimate gas/transaction fees, and broadcast signed transactions to the blockchain. Trigger words: swap, trade, exchange, buy token, sell token, convert, swap tokens, trade tokens, exchange tokens, buy crypto, sell crypto, get a quote, swap quote, price quote, how much will I get, swap rate, exchange rate, slippage, swap route, best price, execute swap, confirm swap, make a trade, place a trade, transaction, send transaction, broadcast, submit transaction, tx, send tx, gas fee, transaction fee, fee estimate, gas estimate, how much gas, supported chains, swap chains, which chains, available tokens, swap tokens, chain list, token list, build transaction, sign transaction. Chinese: 兑换, 交易, 买入, 卖出, 换币, 代币兑换, 报价, 兑换报价, 价格, 能换多少, 滑点, 路由, 最优价格, 执行交易, 确认交易, 发送交易, 广播交易, 手续费, Gas费, 费用估算, 支持的链, 可用代币, 构建交易, 签名交易. CRITICAL: Always use `--json` flag for structured output. CRITICAL: Swap amounts are in **smallest unit** (e.g. lamports for SOL, wei for ETH). CRITICAL: ALWAYS run `lfi token security` on the target token BEFORE executing a swap. CRITICAL: NEVER execute swap or send transaction without explicit user confirmation. Do NOT use this skill for: - Token search, info, security audit, K-line → use liberfi-token - Trending tokens or new token rankings → use liberfi-market - Wallet holdings, activity, or PnL stats → use liberfi-portfolio - Token holder or trader analysis → use liberfi-token Do NOT activate on vague inputs like "trade" or "buy" without specifying tokens or amounts.
Query and handle security risk events from Alibaba Cloud Data Security Center. Supports viewing the list of unprocessed risk events and performing manual handling operations on risk events. Trigger words: "Data Security Center", "security risk events", "DSC", "risk handling", "DescribeRiskRules", "PreHandleAuditRisk"
Expert skill for Datadog Observability & Security Platform
Activate when the user asks Claude to talk like a caveman, use caveman mode, say "less tokens please", or invoke "/elastic-caveman". Also activate when the user wants faster, terser responses while still working with Elasticsearch, Kibana, Elastic Security, Elastic Observability, or any part of the Elastic stack. In caveman mode all Elasticsearch-specific technical terms, API names, field names, index patterns, query DSL structures, ESQL syntax, and error messages are preserved verbatim — only filler words and pleasantries are removed. Stop caveman mode when the user says "stop caveman" or "normal mode".
Platform-agnostic OWASP secure coding practices with JavaScript/Node.js patterns and NetSuite SuiteScript examples. Covers Open Worldwide Application Security Project (OWASP) Top 10 (2021), output encoding, injection prevention, CSP headers, file security, API hardening, AI agent security, DRY security patterns, and 48+ security pitfalls with GOOD/BAD code templates.
Technical due diligence for M&A, investment, or acquisition. Reads a target company's codebase and generates a comprehensive tech DD report with architecture assessment, tech debt quantification, scalability analysis, security posture, team capability inference, build system quality, test coverage, deployment maturity, and open source license risks. Outputs tech-dd-report.md formatted like a real investment memo with risk ratings, remediation costs, and go/no-go recommendation.
Guides VP-level cloud program leadership—multi-year cloud strategy and migration/modernization portfolio, landing zone and CCoE operating model at org scale, hyperscaler enterprise agreement and commit governance, hybrid/multi-cloud posture, cloud center of excellence and talent, and board/CFO/CTO cloud narratives. Use when setting cloud direction, prioritizing migration waves, governing EA/MACC and cloud spend envelope, designing federated cloud org model, steering CCoE and standards adoption, preparing executive or board cloud updates, or adjudicating product vs platform vs security cloud trade-offs—not for Terraform/K8s implementation (cloud-engineer, infrastructure-engineer), landing zone technical design (enterprise-cloud-architect, cloud-architect), monthly CUR FinOps (finops-analyst), TCO/NPV modeling (cloud-economist), full infra portfolio including DC capex (vp-of-infrastructure), or GL close (compute-accounting-manager).
Guides AI ops leadership—LLM SRE, model/prompt releases, eval/incidents, cost/capacity, vendors, and cross-functional cadence. Use for AI platform ops, LLM SLAs, incidents, rollout governance, unit economics, red-team/eval gates, and team rituals—not memory (ai-memory-developer), context code (ai-context-engineer), security programs (cybersecurity), token roadmaps (ai-token-improvement-plan-engineer), solution architecture (applied-ai-architect-commercial-enterprise), skills portfolio (ai-skill-manager), or vertical AI product eng management (engineering-manager-vertical-ai-products). Prompt/eval team management and golden-set release policy: engineering-manager-agent-prompts-evals. Safeguard inference platform: ml-infrastructure-engineer-safeguards. Safeguard model research: ml-research-engineer-safeguards.
Server-authoritative networking, RemoteEvent validation, rate limiting, exploit prevention, security hardening.
Pre-processes the repository by generating security-focused summaries (mantis-summary.md) for each directory to make planning and research more efficient. Use when starting a review campaign to map the codebase before threat modeling and planning. Don't use for executing code reviews, writing test scripts, or patching code.
Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).