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Found 1,657 Skills
Create visually strong landing pages, websites, and app UIs with restrained composition. OpenAI's production frontend playbook.
Machine-learning prediction strategy framework via Longbridge Securities — walk-forward rolling training with feature engineering (MACD, RSI, Bollinger Band width, volume change rate) and a scikit-learn classifier (Random Forest / Gradient Boosting); retrains every 60 days, predicts 5-day direction; buy signal when probability > 0.6, sell when < 0.4; evaluates win rate, profit factor, and Sharpe ratio. Triggers: "机器学习", "ML策略", "预测模型", "随机森林", "梯度提升", "深度学习", "AI选股", "walk-forward", "機器學習", "ML策略", "預測模型", "隨機森林", "梯度提升", "machine learning", "ML strategy", "predictive model", "random forest", "gradient boosting", "AI stock selection", "walk-forward", "rolling training", "feature engineering", "scikit-learn", "XGBoost".
Security best practices for Azure DocumentDB — TLS enforcement, Private Endpoint / firewall configuration, Microsoft Entra ID + RBAC for authentication, and customer-managed keys (CMK) for encryption at rest. Use when reviewing production security posture, configuring networking, setting up authentication / authorization, or preparing for compliance audits.
Guides failure-prevention culture and operational excellence for mission-critical engineering— zero-defect aspiration vs error budgets; HRO principles; defense-in-depth; fail-safe/fail-closed; verification gates and independent checks; redundancy and graceful degradation; pre-mortems and FMEA; stop-the-line; defect escape, near-miss, and repeat-incident metrics; leadership against normalization of deviance—not blame culture. Use for failure-prevention programs, HRO practices, verification gates, fail-safe design, pre-mortem/FMEA, stop-the-line, near-miss reporting, or defect-escape metrics—not SRE error budgets only (site-reliability-engineer), incident command only (incident-management-engineer), backup/restore only (cyber-resilience-engineer), CI lint only (build-validator), agile coaching, HR discipline, or classified ATO without ops-excellence lens (classified-cyber-security-senior-manager).
Convert Markdown articles into inline-style HTML compatible with WeChat Official Accounts. It uses the kami paper-style theme by default, and supports switching between multiple themes including kami, magazine-ink, magazine-indigo, magazine-forest, magazine-kraft, magazine-dune, elegant, modern, and minimal, as well as parameter configurations such as font, font size, accent color, background color, and output path. It is used for official account typesetting, article HTML generation, and replacing unstable external typesetting services, and is especially suitable for converting articles in this vault into a format that can be copied to the WeChat Official Account editor.
Verify a claim with fresh local evidence: restate it falsifiably, capture baseline and treatment, compare artifacts, and return VERIFIED, NOT VERIFIED, or INCONCLUSIVE.
Extract Feishu (Lark) Docs, Wiki pages, Wiki collections/hubs, spreadsheets, and Minutes (妙记) transcripts into clean high-fidelity local Markdown. The primary path is the lark-cli API — programmatic extraction with no LLM rewriting of the body — which recursively follows a collection's reference graph (mention-doc / sheet / cross-tenant links) and uses error codes to resolve permission boundaries precisely; a browser-DOM path is the fallback only when lark-cli cannot reach the content. Use this whenever the source is a Feishu/Lark URL and fidelity matters — including 导出飞书文档/合集/妙记转写, 把飞书 wiki/知识库转 markdown, scraping or archiving a Feishu collection, exporting a Feishu Minutes/妙记 transcript, or saving a Feishu page locally — even if the user only says clipping, archiving, converting, or "save this". Also covers the permission-denied path (owner-exported .docx → faithful Markdown with heading/highlight restoration).
Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group analysis via Longbridge. Frameworks: investment proposals, coverage initiation, stock research, competitive analysis, financial planning, and DeFi/on-chain analysis. Triggers: "机构评级", "目标价", "一致预期", "EPS预测", "内部人交易", "空头", "行业排名", "投资提案", "首次覆盖", "竞争格局", "财务规划", "DeFi收益", "链上数据", "機構評級", "目標價", "一致預期", "內部人交易", "空頭", "投資提案", "首次覆蓋", "競爭格局", "鏈上數據", "analyst rating", "price target", "consensus", "insider trades", "short interest", "coverage initiation", "DeFi yield", "on-chain", "earnings calendar", "finance calendar", "财报日历", "下周谁财报", "下周财报", "下周有哪些财报", "哪些财报", "谁财报", "FOMC", "非农", "股东", "谁持有", "股東", "基金持仓", "基金持倉", "機構評級", "目標價", "財務規劃"
Buy one of the 8 ad squares on frontpage.sh — pay USDC on Tempo via MPP, two HTTP calls, no accounts. Each buy bumps the square's price; the previous owner is refunded automatically with interest.
List channels, read recent messages, and send messages on Discord using the user's own bot, via the Discord REST API. Use when the user wants their Discord BOT to post a message, read a channel, or list servers/channels — anything that acts in a server the bot was invited to.
Writes, rewrites, diagnoses, and improves any LLM prompt with minimal, high-signal edits. Use when the user wants to create a new prompt from scratch, review or fix a prompt that produces poor output, simplify or tighten instructions, restructure a long prompt, port a prompt between models, or expand an existing prompt. Covers system prompts, agent instructions, CLAUDE.md rules, SKILL.md prompt bodies, chat templates, structured-output prompts, RAG context templates, and prompt strings embedded in code. Also use when editing any file whose primary content is LLM instructions.
Design and implement GraphQL APIs with schema design, resolvers, queries, mutations, subscriptions, and best practices. Use when building GraphQL servers, designing schemas, or migrating from REST to GraphQL.