Fetch and read U.S. institutional 13F-HR filings (quarterly long-equity holdings) for any fund manager from SEC EDGAR — free, no API key. Resolve a fund to its filing entity (CIK), pull the latest or a historical quarter's holdings as a ranked CSV with values normalized to whole dollars and positions rolled up by issuer, and interpret them without the common traps. Triggers: "get the 13F for X", "latest 13F holdings of Y", "what does <fund> own", "pull <manager>'s 13F", "find the CIK for <fund>", "who filed this 13F", "13F analysis of Z".
Shared runtime for Analyst Kit skills: the ~/.analyst-kit data home, config store, local usage analytics with opt-in telemetry, daily update checks, and a per-user learnings log every skill reads and appends to. Loaded automatically as a dependency of every other skill. Triggers: "set up analyst-kit", "help me set up Analyst Kit", "configure all skills", "analyst-kit config", "enable/disable a skill", "check for analyst-kit updates", "upgrade analyst-kit skills", "show my analyst-kit learnings", "turn analyst-kit telemetry on/off", "show my analyst-kit usage".
How to structure any financial analysis before fetching a single number: decide the deliverable (report/deck vs financial-model update), align fiscal calendars and data frequencies, normalize units, route each data series to the right skill, and apply sector-specific conventions (reporting calendars, KPIs, seasonality, valuation norms) from per-sector playbooks loaded on demand. Triggers: "how should I structure this analysis", "compare X and Y", "analyze <company> properly", "what matters for this sector", "which metrics should I use for X", "build an analysis plan for Y".
Calculate and interpret key financial ratios from financial statement data (income statement, balance sheet, cash flow, market data) for investment analysis — profitability (ROE, ROA, margins), liquidity (current/quick/cash), leverage (debt-to-equity, interest coverage), efficiency (asset/inventory/ receivables turnover), valuation (P/E, P/B, P/S, EV/EBITDA, PEG), and per-share metrics, with industry-standard interpretation and benchmarking. Pure-stdlib Python, fully offline — no API key. Triggers: "calculate financial ratios for X", "what's the P/E / ROE / debt-to-equity of Y", "analyze the liquidity / leverage / profitability of Z", "interpret these financial statements", "ratio analysis on this balance sheet", "is this company's margin / coverage healthy", "benchmark <company>'s ratios".
Build financially-correct charts from company fundamentals — pick the right chart for the question, normalise units (one unit per axis, $B/$M scaling, %-vs-$ dual axes, rebasing for comparisons), and apply finance conventions (green beat / red miss, accounting negatives, dashed estimates, dark totals). A thin Python+Polars layer normalises already-available data into a chart contract; a TypeScript layer emits Highcharts options and renders a self-contained HTML page. Covers revenue trends & YoY, segment mix, margins, dividends, earnings surprise, estimate-vs-reported, revenue→net-income waterfalls, and price (candlestick/Stock). Use whenever the user wants to chart, plot, graph, or visualize financial data. Triggers: "chart revenue over time", "plot YoY growth with event flags", "revenue breakdown by segment", "dividend history and yield", "earnings surprise chart", "estimate vs reported", "waterfall from revenue to net income", "margins over time", "candlestick / price chart", "compare two companies' revenue
Own a watchlist ("universe") of companies and everything time-based about them. Maintain the roster (add / update / soft-delete / reactivate / list with metadata, competitors, rationale) and track each company's key dates — earnings, investor days, ex-dividend, AGMs, conferences, guidance, lockups. Run a daily monitor that re-fetches dates and detects what changed (earnings moved, newly announced, confirmed-from-estimated, dropped), and produce a daily brief (key-date changes, upcoming calendar, news + 8-K material events) as markdown or a branded PDF. Storage is pluggable behind one contract: a local folder (~/company-universe) or a connected server (e.g. Google Sheets over MCP). Triggers: "add company to my universe / watchlist", "list my companies", "when does X report earnings", "track earnings / ex-dividend dates for Y", "what changed in earnings dates", "any investor days coming up", "run the daily universe monitor", "daily brief / report for my watchlist", "schedule the daily check", "upcoming key date
Build a comprehensive, multi-page company research wiki as a deployed web application. Use for: researching any publicly listed company from any region (US, Europe, Japan, Taiwan, India, or other) and producing a structured wiki covering company overview/history, individual product pages (sourced from earnings calls and investor presentations), 5-year financials, analyst reports, stock price and technical analysis, financial modelling with growth scenarios and forward P/E and P/S multiples, competitor comparison, and a sourced citations page. The wiki is built with React + Tailwind using the webdev tools and deployed on Manus hosting. Triggers: 'build a company wiki for X', 'research wiki on Y', 'make a company research site for Z', 'deep research wiki for <ticker>'.
Build financial models for investment decisions: complete DCF valuations (FCF projections, WACC via CAPM, terminal value via perpetuity growth or exit multiple, enterprise/equity value, per-share value), M&A merger models (accretion/dilution to acquirer EPS, stock-vs-cash consideration, financing drag, purchase-price-allocation intangible amortization, breakeven synergies), sensitivity analysis (one-way and two-way data tables, tornado charts, breakeven search), and probability-weighted best/base/worst scenario planning. Runs locally in Python (numpy + pandas) — no API key. Triggers: "build a DCF model for X", "what's the intrinsic / fair value of Y", "DCF / discounted cash flow valuation", "is this acquisition accretive or dilutive", "merger model / accretion-dilution for X buying Y", "pro forma EPS of this deal", "what synergies does this deal need to break even", "sensitivity analysis on growth rate and WACC", "tornado chart of value drivers", "breakeven WACC / growth for this valuation", "best/base/worst