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Found 523 Skills
Deep Angular 21 clean code audit with parallel specialist agents and senior team lead. Scans architecture, signals, stores, AI slop, ViewModel patterns, and more. Guarantees craftsman-level output. Use whenever the user says 'clean code', 'audit Angular', 'review frontend', 'check quality', 'anti-patterns', wants Angular code reviewed, or needs senior-level code standards enforced — even if they don't say 'clean code' explicitly.
Activate this when users need to understand extreme events (bubbles, crashes, mass hysteria, cults, mob behavior), diagnose systemic organizational failures, or assess the risk of multiple psychological/market/institutional forces aligning in the same direction. Typical trigger signals: the phenomenon described by the user "far exceeds what any single factor can explain"; the user attempts to explain an extreme outcome with a single cause; the user is concerned about "multiple adverse factors erupting simultaneously". Not applicable to conventional single-factor decision analysis or assessment of mild incremental changes.
Build creator lead lists for TikTok, Instagram, and X by turning normalized platform datasets into outreach-ready leads with contact signals, shortlist logic, and draft outreach messages. Use this when the user wants creator discovery, contact extraction, shortlist building, or outreach prep.
Detect buying signals from multiple sources, qualify leads, and generate outreach context
Cross-functional organizational health check combining signals from all C-suite roles. Scores 8 dimensions on a traffic-light scale with drill-down recommendations. Use when assessing overall company health, preparing for board reviews, identifying at-risk functions, or when user mentions org health, health check, or health dashboard.
Crypto market-structure research agent — 24+ indicators across derivatives, options (gamma wall, skew), on-chain (MVRV, smart money signals, DEX hot tokens), and macro sentiment. Powered by OKX CeFi CLI + OnchainOS + direct HTTP for options chain. Use this skill whenever the user asks about: derivatives data, gamma wall, options skew, funding rates, open interest, put/call ratio, MVRV, cost basis, realized price, exchange flows, CEX inflows/outflows, liquidation pressure, whale tracking, smart money flows, fear/greed index, BTC dominance, stablecoin flows, taker volume, basis/backwardation, or any request like "what does the market structure look like", "give me a macro overview", "how are derivatives positioned", "is the market overleveraged", "should I be bullish or bearish based on data", "are whales accumulating or distributing", "show me exchange flows". Also trigger when users mention specific tokens and want deeper analysis beyond simple price action — e.g., "what's going on with ETH right now", "is BTC about to move", "analyze SOL market conditions".
Control Ableton Live with AI agents via MCP - create MIDI clips, insert audio, add tracks/devices, analyze signals, automate mixing
For post-market review, focusing on daily review / market research / transaction summary. This Skill is mainly used in scenarios such as answering user questions, writing reports, and creating financial articles. This report generates a large amount of output and is not suitable for simple conversation scenarios. For obtaining various information and data, you can use the wind.financial.data tool with appropriate keywords or keyword combinations. After the market closes, you need to quickly review the entire day's market to understand what happened, which signals are worthy of attention, and how to respond tomorrow.
Use when adding, modifying, optimizing, or debugging CuTile autotuning code. Trigger signals: `exhaustive_search` / `replace_hints` / `hints_fn` / `cuda.tile.tune` in code, `autotune` in filenames, or correctness/performance issues in autotuned CuTile kernels. Covers: tune-once/cache/launch pattern, per-architecture configs (sm80–sm120), parameter space design (tile sizes, occupancy, num_ctas), and 7 common pitfalls with solutions.
Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
Add Sumsub Device Intelligence (the Fisherman module) to a web project that already verifies users with the Sumsub WebSDK. TRIGGER when the user asks to "add device intelligence", "enable device capture / fingerprinting in the WebSDK", "turn on Fisherman", "detect device fraud / multi-accounting in the verification flow", or asks how device risk labels get onto an applicant verified through the WebSDK. Covers the whole loop — enabling Capture device data on the level, the automatic in-SDK Fisherman lifecycle, the advanced self-rendered wiring, reading device signals (Devices tab, Device Check, risk labels, webhooks), sandbox testing, go-live checklist. SKIP for device intelligence on pages with NO WebSDK widget (login / signup / checkout) — use `sumsub-integrate-dint-standalone`; SKIP for the base WebSDK embed itself — use `sumsub-integrate-websdk`.
Use this skill to validate code changes against real Kubernetes microservice dependencies with Signadot signals such as local sandboxes, cluster reachability, logs, endpoints, and routing-key isolation.