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Found 540 Skills
Analyze broker-dealer recommendations under SEC Regulation Best Interest's four obligations: Disclosure, Care, Conflict of Interest, and Compliance. Use when the user asks whether a recommendation satisfies Reg BI, what triggers the 'recommendation' standard, how to evaluate reasonably available alternatives, rollover recommendation compliance, dual-registrant capacity disclosure, share class or account type recommendations, or Reg BI examination preparation. Also trigger when users mention 'best interest standard for brokers', 'is this a Reg BI recommendation', 'care obligation documentation', 'sales contest elimination requirement', 'Form CRS delivery', or ask how Reg BI differs from suitability or fiduciary duty.
Build and operate predictive models for logistics networks—demand forecasting at SKU/location/lane granularity; inventory positioning and safety stock optimization interfaces; ETA and lead-time prediction; capacity and congestion signals; route and network flow forecasting at model-integration level; cold chain and perishables; promotion and seasonality; model monitoring, drift, and backtesting against operational KPIs (fill rate, OTIF, WMAPE/MAPE). Use for predictive logistics, demand forecasting logistics, ETA prediction, inventory positioning, safety stock optimization, OTIF forecast, lane demand, WMAPE, logistics ML, capacity forecasting logistics, or cold chain forecast—not pure OR/MIP without logistics domain (operations-research-algorithm-developer), supply chain strategy only (supply-chain-manager), WMS feature dev (wms-developer), fleet telematics ingestion (geospatial-telematics-developer), generic ML without logistics (data-scientist), or EDI document mapping (edi-engineer).
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Evidence-based investigative code review using deductive reasoning to determine what actually happened versus what was claimed. Use when verifying implementation claims, investigating bugs, validating fixes, or conducting root cause analysis. Elementary approach to finding truth through systematic observation.
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, designing systems, or making architectural decisions. Enters plan mode, reads all available docs, explores the codebase deeply, then interviews the user relentlessly with ultrathink-level reasoning on every decision until a shared understanding is reached. Produces a validated design spec before any implementation begins. Triggers on feature requests, design discussions, refactors, new projects, component creation, system changes, and any task requiring design decisions.
Use when cognee is a Python AI memory engine that transforms documents into knowledge graphs with vector and graph storage for semantic search and reasoning. Use this skill when writing code that calls cognee's Python API (add, cognify, search, memify, config, datasets, prune, session) or integrating cognee-mcp. Covers the full public API, SearchType modes, DataPoint custom models, pipeline tasks, and configuration for LLM/embedding/vector/graph providers. Do NOT use for general knowledge graph theory or unrelated Python libraries.
Implement and configure Syncfusion MultiColumnComboBox control in Windows Forms - an advanced combobox with multiple columns in dropdown and virtual data binding for large datasets. Use when creating dropdown lists with multiple data fields, DataSource binding, DisplayMember/ValueMember configuration, or column headers in dropdown. Covers filtered dropdown lists and replacing standard ComboBox with multi-column alternatives.
Expertise in F2P economics, virtual currencies, and ethical monetization strategiesUse when "game monetization, F2P economy, in-app purchase, IAP strategy, battle pass design, loot box, gacha system, virtual currency, player LTV, whale monetization, game economy balance, premium currency, season pass, daily rewards, pay to win, ethical monetization, monetization, f2p, free-to-play, iap, in-app-purchase, battle-pass, season-pass, gacha, loot-box, virtual-economy, game-economy, ltv, arpu, retention, whales, pricing, microtransactions" mentioned.
Use when planning promotional activities on Xiaohongshu, designing marketing campaigns, organizing contests and giveaways, creating holiday or seasonal promotions, or coordinating interactive events to boost engagement
MLA (Multi-Latent Attention) cost models, regime analysis, and kernel selection guide. Use when: (1) reasoning about which kernel approach to use for a given regime, (2) understanding cost model tradeoffs between FlashMLA, FlashAttention, and MLAvar6+, (3) analyzing roofline behavior across decode/speculative/prefill regimes, (4) setting optimization targets, (5) understanding MLA math and absorption trick.
Documents the reasoning behind design decisions including alternatives considered, trade-offs evaluated, and principles applied. Use when making significant UX decisions, aligning with stakeholders on design direction, or preserving design context for future reference.
Classify a PPT brief into one of four types (Pitch / Research / Teaching / Narrative), then generate a high-level chapter skeleton personalized to the topic for that type. Different PPT types require different argumentation frameworks and different chapter structures — a research PPT is not a pitch, and a pitch is not a narrative. Use this at the very start of PPT planning, before formulating the thesis. It pairs with ppt-research-setup and other type-specific setup skills for detailed per-chapter reasoning.