Agent skill · business finance · daymade
financial-data-collector
Collects real financial data for any US publicly traded company from free public sources (yfinance) and outputs structured JSON for downstream skills (DCF modeling, comps analysis, earnings review): market data, historical financials, WACC inputs, analyst estimates — never fabricated fallback values. Use to collect or pull financial/market data, or gather DCF inputs, for a ticker.
Why this skill is useful
Adds executable scripts for collecting and validating financial data from yfinance, which are not commonly available in public documentation.
What it needs
Requires python installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 1,320 stars on the source repository.
What this skill does
Financial Data Collector Collect and validate real financial data for US public companies using free data sources. Output is a standardized JSON file ready for consumption by other financial skills. Critical Constraints NO FALLBACK values. If a field cannot be retrieved, set it to null with source: "missing". Never substitute defaults (e.g., beta or 1.0). The downstream skill decides how to handle missing data. Data source attribution is mandatory. Every data section must have a source field. CapEx sign convention: yfinance returns CapEx as negative (cash outflow). Preserve the original sign. Document the convention in output metadata. Do NOT flip signs. yfinance FCF ≠ Investment bank FCF. yfinance FCF = Operating CF + CapEx (no SBC deduction). Flag this in output metadata so downstream DCF skills don't overstate FCF. Workflow Step 1: Collect Data Run the collection script: The script collects in this priority: 1. yfinance — market data, historical financials, beta, analyst estimates 2. yfinance ^TNX — 10Y Treasury yield as risk-free rate proxy 3. User supplement — for years where yfinance returns NaN (report to user, do not guess) Step 2: Validate Data Checks: field completeness, cross-field consistency (Market Cap = Price × Shares), range sanity (WACC 5-20%, beta 0.3-3.0), sign conventions. Step 3: Deliver JSON Single file: {TICKER}financialdata.json. Schema in references/output-schema.md. Do NOT create: README, CSV, summary reports, or any auxiliary files. Output Schema (Summary) Full schema with all field definitions: references/output-schema.md <correctpatterns> Handling Missing Years CapEx Sign Preservation Datetime Column Indexing Field Name Guards </correctpatterns> <commonmistakes> Mistake 1: Default Values for Missing Data Mistake 2: Assuming All Years Have Data Mistake 3: Using yfinance FCF in DCF Models Directly yfinance FCF does NOT deduct SBC. For mega-caps like META, SBC can be $20-30B/yr, making yfinance FCF ~30% higher than investment-bank FCF. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills daymade/financial-data-collector