vibe-investing

Automatically analyze a company or company-related finance situation from a short user prompt such as a company name, "analyze [company]," M&A, LBO, IPO, debt, credit, or risk requests. Use when an agent must infer the correct valuation and finance framework without asking follow-up questions, begin from market-implied expectations instead of immediate fair value, run Reverse DCF before Forward DCF for listed companies, perform web-verified data gathering and deal-radar checks, defend against hallucinations with explicit data tags and uncertainty statements, and produce a plain-text output with no markdown and no row-column tables.

Fetch financial, market, economic, fundamental, news, options, crypto, ETF, index, and macro data through the OpenBB Python interface instead of the OpenBB MCP server. Use when an agent needs current or historical data from OpenBB-supported providers, needs to replace OpenBB MCP calls with direct Python/OpenBB usage, or must return source-tagged, reproducible datasets with clear query parameters, provider details, and data-quality notes.

Analyze a company, sector situation, or valuation question through Aswath Damodaran's lens. Use when the analysis should start with the business story, connect that story to revenue growth, margins, reinvestment, and risk, then judge valuation through disciplined intrinsic-value work, expectation testing, and explicit uncertainty rather than slogan-level cheap or expensive language.

Analyze an investment through Benjamin Graham's conservative value-investing lens. Use when the analysis should focus on margin of safety, balance-sheet strength, earnings stability, Graham-style valuation measures such as Graham Number or net-net logic, and avoidance of speculation or aggressive growth assumptions.

Analyze an investment through Bill Ackman's concentrated activist lens. Use when the analysis should focus on high-quality businesses, durable moats, free-cash-flow generation, capital allocation, valuation support, and the presence or absence of catalysts, strategic change, or activist-style value creation.

Analyze an investment through Cathie Wood's disruptive-innovation lens. Use when the analysis should focus on breakthrough technology, large total addressable markets, multi-year growth optionality, platform scalability, and management willingness to invest in R&D even when near-term volatility or valuation looks uncomfortable.

Analyze an investment through Charlie Munger's quality-first lens. Use when the analysis should emphasize durable business quality, incentives, management character, capital allocation, multidisciplinary thinking, avoidance of complexity or fragility, and willingness to pay a fair price for an exceptional business rather than a bargain price for a weak one.

Analyze an investment through Michael Burry's hard-number contrarian lens. Use when the analysis should focus on deep value, downside protection, balance-sheet skepticism, free-cash-flow and EV-based valuation, market overreaction, and the presence of concrete catalysts such as insider buying, asset sales, buybacks, or forced unwinds.

Analyze an investment through Mohnish Pabrai's Dhandho-style lens. Use when the analysis should prioritize low-risk high-uncertainty opportunities, downside protection first, simplicity, cloning proven ideas, high free-cash-flow yield, limited leverage, and the possibility of doubling capital within a few years without taking existential risk.

Analyze an investment through Nassim Taleb's antifragility and tail-risk lens. Use when the analysis should focus on fragility versus antifragility, convexity, downside asymmetry, skin in the game, hidden blow-up risk, and whether volatility, leverage, or optimization makes the opportunity more dangerous than it first appears.

Analyze an investment through Peter Lynch's practical growth-at-a-reasonable-price lens. Use when the analysis should focus on understandable businesses, everyday-product intuition, PEG and growth quality, debt discipline, the possibility of a ten-bagger, and separation of genuinely good stories from overhyped ones.

Analyze an investment through Phil Fisher's scuttlebutt-driven growth lens. Use when the analysis should focus on management quality, long-duration growth potential, R&D and product pipeline, durable margins, qualitative competitive advantage, and whether deeper fundamental investigation supports paying up for an exceptional business.

Analyze an investment through Rakesh Jhunjhunwala's long-term growth-and-value lens. Use when the analysis should focus on circle of competence, economic moat, management quality, financial strength, margin of safety, return metrics such as ROE, and whether the business can create long-term wealth rather than short-term trading excitement.

Analyze an investment through Stanley Druckenmiller's asymmetric-opportunity lens. Use when the analysis should focus on growth, momentum, sentiment, macro or narrative inflection, catalyst paths, downside control, and whether the opportunity offers enough upside asymmetry to justify acting with conviction while remaining willing to cut the thesis if conditions change.

Analyze an investment through Warren Buffett's long-term quality-and-value lens. Use when the analysis should stay inside circle of competence, emphasize moat, management quality, financial strength, intrinsic value versus price, and durable long-term compounding rather than short-term trading narratives or speculative upside.

Analyze traditional market context for an investment case by identifying the current regime, cycle position, market expectations, liquidity and macro transmission, positioning and crowd psychology, risk asymmetry, and reflexive feedback loops between price, narrative, financing, and fundamentals. Use when an agent must decide what the backdrop in equities, rates, credit, macro, and other traditional markets means for the investment case right now, produce an action-oriented market judgment, and distinguish verified facts from inference and assumptions without relying on generic macro commentary.

Design, evaluate, and challenge quantitative investment ideas using an integrated research workflow that covers factor and asset-pricing logic, signal generation, signal validation, backtesting, overfitting defense, technical-analysis signals, data hygiene, risk modeling, and performance attribution. Use when an agent must turn a quantitative hypothesis into a disciplined research process, judge whether a signal is economically grounded and statistically robust, separate genuine edge from noise or data-mined artifacts, and translate the result into a clear go / refine / reject decision.

Package investing analysis into a publishable financial-report style with institutional section flow, thesis framing, valuation context, catalysts, risks, tables, and financial charts. Use when an agent needs to turn existing research into a broker-style or professional finance report for equities, crypto, credit, commodities, portfolios, or macro topics, including chart-heavy outputs such as indicator charts, OHLCV charts, line charts, bar charts, pie charts, and comparison visuals, while keeping the result structured enough for an external docx, pdf, markdown, or spreadsheet skill to render final files.