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Found 579 Skills
Diagnose and manage Alibaba Cloud databases through natural language. Use when users need to troubleshoot database performance issues (high CPU, slow queries, abnormal connections, lock waits), check instance status, analyze disk space, optimize SQL, run health inspections, or detect security baseline violations. Supports RDS (MySQL/PostgreSQL/SQL Server), PolarDB, MongoDB, Redis (Tair), and Lindorm. Trigger this skill even for casual descriptions like "my database is slow", "can't connect to the database", "help me check this SQL", or "database disk is almost full". Also suitable for consulting Alibaba Cloud-specific database features (e.g., PolarDB Serverless, DAS autonomy capabilities) and comparing product differences (RDS vs PolarDB). Do NOT use this skill for general SQL tutorials, non-Alibaba Cloud databases, or local database administration.
Profile-driven performance optimization with behavior proofs. Use when: optimize, slow, bottleneck, hotspot, profile, p95, latency, throughput, or algorithmic improvements.
Detect and remove AI-generated writing patterns from text while preserving semantic meaning and factual accuracy. Rewrites text to sound natural, varied, and human-authored across domains including academic, technical, blog, professional, and social media writing. Use this skill when the user asks to "humanize text", "make this sound human", "remove AI patterns", "rewrite to sound natural", "make this less AI", "de-slop this", "clean up AI writing", "make this not sound like ChatGPT", or provides AI-generated text and asks for a natural rewrite. Also trigger when reviewing drafts for AI tells, checking if text sounds AI-generated, or requesting a "human pass" on content.
Find composition and state-lifting refactor opportunities in a React codebase. Audits for boolean-prop bloat, monolith components with variant explosion, sibling clusters that should share lego-brick subcomponents, render-prop slots that can't reach outside the box, and state synced between siblings via useEffect. Use when the user wants to improve react code, audit react components, find react refactor opportunities, run a react composition review, or asks "improve react", "audit react", "react architecture review".
HertzFlow on-chain trade-decision intelligence. Currently covers Binance Alpha forensic across all surf-SQL EVM chains (BSC / Ethereum / Arbitrum / Base / Polygon / Optimism) — insider distribution, 真实派发 confirmed sell-out, 筹码三分法 (operator / CEX pool / verifiable retail), anomaly waves, monitoring exports. Solana runs in HOLDER_SNAPSHOT mode. Auto-trigger whenever the user pastes a raw 0x-prefixed 40-hex EVM CA, a Solana base58 CA, mentions a Binance Alpha token by ticker, or asks about 链上 forensic / 内幕出货 / 派发 / chip structure / quiet insider / Alpha distribution / on-chain dump — even if they don't say "hertzflow" explicitly. Pipeline runs deterministically (~2-10 min per CA depending on activity + surf cache state); LLM only fills narrative slots, never picks the verdict or writes SQL. Perp metrics, bridge audits, and HertzFlow core contract analysis sub-domains are coming — when those ship, this skill will dispatch to them based on input pattern (perp symbol, bridge protocol name, etc.) using the router table below. REQUIRES a Surf account + SURF_API_KEY. New users get 2000 free credits (~6-8 reports) via the HertzFlow private invite. Full forensic costs ~$1.5-3 USD per CA in Surf credits after the free tier runs out.
Decide per SKU whether to remove, liquidate, dispose, or keep aging FBA inventory. Breaks the math: base storage plus the monthly aged-inventory surcharge over the holding horizon vs removal fees vs recoverable resale value. Use when a user asks about aged inventory, aged-inventory surcharge, long-term storage fees, removal orders, liquidation, or what to do with slow movers. Trigger phrases: "aged inventory", "aged-inventory surcharge", "long-term storage", "removal order", "liquidate", "slow movers", "dispose", "old stock". Works with zero tools. the user provides unit cost, age, storage rate, and current price.
Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.
Analyze and optimize SQL queries for performance. Use when improving slow queries, reducing execution time, or analyzing query performance in PostgreSQL and MySQL.
Use when app feels slow, memory grows, battery drains, or diagnosing ANY performance issue. Covers memory leaks, profiling, Instruments workflows, retain cycles, performance optimization.
Expert-level Rust performance optimization guidelines for build profiles, allocation, synchronization, async/await, and I/O. This skill should be used when writing, reviewing, or optimizing Rust code for performance. Triggers on tasks involving slow Rust code, large binary size, long compile times, LTO configuration, release profile tuning, allocation reduction, clone avoidance, lock contention, BufReader/BufWriter, flamegraph analysis, async runtime issues, Tokio performance, spawn_blocking, parking_lot vs std sync, or any Rust performance investigation.
ONLY use when user explicitly says 'deep research', 'exhaustive', 'comprehensive report', or 'thorough investigation'. Slower and more expensive than parallel-web-search. For normal research/lookup requests, use parallel-web-search instead.
Expert performance decisions for iOS/tvOS: when to optimize vs premature optimization, profiling tool selection, SwiftUI view identity trade-offs, and memory management strategies. Use when debugging performance issues, optimizing slow screens, or reducing memory usage. Trigger keywords: performance, Instruments, Time Profiler, Allocations, memory leak, view identity, lazy loading, @StateObject, retain cycle, image caching, faulting, batch operations