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Found 81 Skills
Fundamental factor stock screening — filter value or growth stocks using PE, PB, ROE, revenue growth, net-profit growth, and dividend yield across A-share, HK, and US markets. Outputs a candidate table ranked by composite factor score. Triggers: "基本面筛选", "因子选股", "价值选股", "成长选股", "低PE选股", "高ROE", "股息筛选", "PE筛选", "PB筛选", "多条件选股", "基本面因子", "量化选股", "基本面篩選", "因子選股", "價值選股", "成長選股", "低PE選股", "股息篩選", "factor screening", "value screen", "growth screen", "low PE filter", "high ROE screen", "dividend screen", "fundamental factor", "multi-factor stock screen".
Analyze 8-K filings to extract material events and corporate changes using Octagon MCP. Use when tracking real-time corporate disclosures, M&A announcements, leadership changes, earnings releases, and other material events requiring immediate investor attention.
Analyze portfolio allocation drift and generate rebalancing trade recommendations across accounts. Considers tax implications, transaction costs, and wash sale rules. Triggers on "rebalance", "portfolio drift", "allocation check", "rebalancing trades", or "my portfolio is out of balance".
Identify stocks where market sentiment is significantly more negative than fundamentals warrant — the gap between narrative and reality. Use when the user asks to find contrarian opportunities, stocks with sentiment-fundamental misalignment, oversold but fundamentally strong companies, stocks punished by negative narratives, or wants to analyze whether market fear is justified for specific stocks or sectors.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Kerberos, WinRM, SMB, RDP, Windows credential material, replayable tickets, delegation edges, and host-to-host pivot chains. Use when the user asks to replay Kerberos material, trace a WinRM, SMB, or RDP pivot, understand host-to-host privilege movement, or prove which Windows service accepted a credential or ticket. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Agente que simula Warren Buffett — o maior investidor do seculo XX e XXI, CEO da Berkshire Hathaway, discipulo de Benjamin Graham e socio intelectual de Charlie Munger.
Extracts structured practitioner data from healthcare practice websites. Returns names, credentials, specialties, contact info, and education for every provider on a practice's site. Use when user asks to extract, pull, or list doctors, providers, or staff from practice websites. Triggers: "extract doctors from", "pull providers from", "who are the providers at", "build a provider database", "list all doctors at", "scrape the team page", "get practitioner data from". Accepts practice URLs (pasted, CSV, Google Sheet) or discovers practices via Google Maps when given specialty + location. Single sites or 100+ URLs. Do NOT use for filling data gaps — use healthcare-providers-enrich instead. Do NOT use for credential validation — use healthcare-providers-verify instead. Do NOT use for discovering practices — use market-finder or local-places instead. Do NOT use for general extraction — use nimble-web-expert instead.
Buffett-style stock screener — "What would Buffett buy now?" Generates 3–5 candidate stocks from a market / sector / preference query via a two-layer model: hard quant filter (ROE 5y ≥15%, debt/asset ≤50%, FCF positive 3y, listed ≥5y, gross margin ≥30%) → qualitative moat scoring (moat 35% / capital allocation 20% / earnings predictability 20% / valuation 15% / runway 10%). Longbridge CLI first, MCP fallback, WebSearch for gaps only. Output: candidate cards with moat-type tag, quantitative highlights, verdict (🟢 likely buy / 🟡 wait for price / 🔴 not at this price), deep-dive CTA to `longbridge-buffett-moat-analyzer`. Mandatory holding-period education + data-source appendix. Disqualifies airlines, pre-revenue biotech, ST, listing<5y. Triggers: "巴菲特会买什么", "巴菲特选股", "巴菲特风格的股票", "护城河选股", "宽护城河股票", "价值投资选股", "10年不动的股票", "定价权强的公司", "巴菲特會買什麼", "巴菲特選股", "護城河選股", "寬護城河股票", "Buffett screener", "what would Buffett buy", "wide-moat screener", "quality compounder screen", "Berkshire-style screen", "pricing-power screen".
Meta-skill for extracting and creating reusable Claude Code skills from past work sessions. Analyzes git history, code patterns, workflows, and documentation to identify harvestable skills, then generates comprehensive skill definitions with best practices, examples, and structured templates.