MetricDuck — Financial Analysis

Quality 66 / 100needs work

23 tools, about 20,492 tokens to load them all · tool set 026c8756d5f2 · tools last changed 2026-10-19 · checked 2026-10-20 18:38 UTC

Tool changes

• 2026-10-19get_stock_pricechangeddescription
  before

  Daily end-of-day stock prices (open/high/low, close, split- & dividend-adjusted adj_close, volume) for US exchange-listed companies. Sourced from a market-data feed, not SEC filings. Markets are open only on business days, so rows exist ONLY for trading days — the data IS the trading calendar: - Price ON OR AFTER a date (a single date, or an announcement landing on a weekend): pass start_date=<date> alone; the FIRST row of the short forward window is that date or the next open day. - Price ON OR BEFORE a date: pass end_date=<date>; the LAST row is that date or the prior open day. Use Cases: - "AAPL close on 2025-07-28" -> get_stock_price("AAPL", start_date="2025-07-28") - "DKNG total return 2025-01-02 → 2026-02-27" -> get_stock_price("DKNG", start_date="2025-01-02") + get_stock_price("DKNG", end_date="2026-02-27"), first/last close (cheaper than one 14-month window) - "SUI +1/+14/+30 days after an 8-K" -> start_date=<announce>, end_date=<announce + ~32d>; pick rows on/after each - No dates -> the latest price When the window spans ≥2 trading days, the response also reports the first/last close and the period return on BOTH close (point-to-point) and adj_close (split/dividend-adjusted: the economic return). Each response also includes the latest REPORTED period-end shares outstanding on/before your end date (period-end balance-sheet count; dei cover where absent) plus the implied market cap at the latest close — use these for market-cap / EV / P/B math instead of deriving share counts from NI/EPS (that yields weighted-average shares, a different basis). Coverage: ~8,400 US common-equity tickers, end-of-day only (no intraday/real-time, no options/FX). Recent history is dense; deep pre-2014 history may be sparse. Period-end multiples (P/E, EV/EBITDA, P/B): get_metric_history, whose `metric_id` lists the primitives for a CUSTOM multiple (e.g. lease-adjusted EV) priced with this tool.

  after · 97% of words in common

  Daily end-of-day stock prices (open/high/low, close, split-adjusted adj_close (some rows, mostly before Sept 2023, also dividend-adjusted), volume) for US exchange-listed companies. Sourced from a market-data feed, not SEC filings. Markets are open only on business days, so rows exist ONLY for trading days — the data IS the trading calendar: - Price ON OR AFTER a date (a single date, or an announcement landing on a weekend): pass start_date=<date> alone; the FIRST row of the short forward window is that date or the next open day. - Price ON OR BEFORE a date: pass end_date=<date>; the LAST row is that date or the prior open day. Use Cases: - "AAPL close on 2025-07-28" -> get_stock_price("AAPL", start_date="2025-07-28") - "DKNG return 2025-01-02 → 2026-02-27" -> get_stock_price("DKNG", start_date="2025-01-02") + get_stock_price("DKNG", end_date="2026-02-27"), first/last close (cheaper than one 14-month window) - "SUI +1/+14/+30 days after an 8-K" -> start_date=<announce>, end_date=<announce + ~32d>; pick rows on/after each - No dates -> the latest price When the window spans ≥2 trading days, the response also reports the first/last close and the period return on BOTH close (point-to-point) and adj_close (split-adjusted; not a total return). Each response also includes the latest REPORTED period-end shares outstanding on/before your end date (period-end balance-sheet count; dei cover where absent) plus the implied market cap at the latest close — use these for market-cap / EV / P/B math instead of deriving share counts from NI/EPS (that yields weighted-average shares, a different basis). Coverage: ~8,400 US common-equity tickers, end-of-day only (no intraday/real-time, no options/FX). Recent history is dense; deep pre-2014 history may be sparse. Period-end multiples (P/E, EV/EBITDA, P/B): get_metric_history, whose `metric_id` lists the primitives for a CUSTOM multiple (e.g. lease-adjusted EV) priced with this tool.

• 2026-10-18get_filing_sectionchangedinput schema
• 2026-10-17compare_companieschangeddescription
  before

  Compare a company against peers across ~70 curated fundamental metrics (TTM by default; period_type FY or Q for each company's latest fiscal year or quarter), with percentile rankings and relative strengths/weaknesses. Returns a side-by-side table covering valuation (P/E, P/B, EV/EBITDA, EV/Sales, FCF yield), profitability (gross/operating/net/EBITDA margins, ROE, ROA, ROIC), leverage & liquidity (debt/equity, net debt/EBITDA, interest coverage, current ratio), efficiency (asset/inventory turnover, DSO, cash conversion cycle), and capital returns (dividend yield, dividend payout ratio, buyback yield, shareholder yield). Sector-inapplicable metrics are omitted (e.g. gross margin / FCF leverage for banks). Pass 'metrics' to focus the table on specific metric_ids. For one company's value in an older fiscal year/quarter use get_metric_history. Each company's row is dated: 'Data through' is its latest reported period, and valuation multiples are priced at the last close on/before that period end (period-end LOCF) — NOT today's price, and the dates can differ across peers by a quarter. For a multiple AS OF a specific date, or at the live price, or a CUSTOM definition (e.g. lease-adjusted EV), assemble it from get_stock_price (price leg) + get_metric_history primitives. peer_mode controls peer selection: - 'sector' (default): auto-selected from same sector + similar market cap - 'tags': auto-selected by business model similarity (tag Jaccard) — better for cross-sector comparisons Override with custom_peers for specific matchups. The number of custom_peers is capped by plan (Free: 3, Pro: 10); exceeding it returns the limit and the count you asked for, so retry with that many. Use Cases: - "Compare AAPL vs MSFT" -> compare_companies("AAPL", custom_peers="MSFT") - "How does NVDA stack up in its sector?" -> compare_companies("NVDA") - "Dividend payout ratio: KO vs KDP/PEP/KHC" -> compare_companies("KO", custom_peers="KDP,PEP,KHC", metrics="dividend_payout_ratio,dividend_yield")

  after · 99% of words in common

  Compare a company against peers across ~70 curated fundamental metrics (TTM by default; period_type FY or Q for each company's latest fiscal year or quarter), with percentile rankings and relative strengths/weaknesses. Returns a side-by-side table covering valuation (P/E, P/B, EV/EBITDA, EV/Sales, FCF yield), profitability (gross/operating/net/EBITDA margins, ROE, ROA, ROIC), leverage & liquidity (debt/equity, net debt/EBITDA, interest coverage, current ratio), efficiency (asset/inventory turnover, DSO, cash conversion cycle), and capital returns (dividend yield, dividend payout ratio, buyback yield, shareholder yield). Sector-inapplicable metrics are omitted (e.g. gross margin / FCF leverage for banks). Pass 'metrics' to focus the table on specific metric_ids. For one company's value in an older fiscal year/quarter use get_metric_history. Each company's row is dated: 'Data through' is its latest reported period, and valuation multiples are priced at the last close on/before that period end (period-end LOCF) — NOT today's price, and the dates can differ across peers by a quarter. For a multiple AS OF a specific date, or at the live price, or a CUSTOM definition (e.g. lease-adjusted EV), assemble it from get_stock_price (price leg) + get_metric_history primitives. peer_mode controls peer selection: - 'sector' (default): auto-selected from same sector + similar market cap - 'tags': auto-selected by business model similarity (tag Jaccard) — better for cross-sector comparisons Override with custom_peers for specific matchups. The number of custom_peers is capped by plan (Free: 3 peers); exceeding it returns the limit and the count you asked for, so retry with that many. Use Cases: - "Compare AAPL vs MSFT" -> compare_companies("AAPL", custom_peers="MSFT") - "How does NVDA stack up in its sector?" -> compare_companies("NVDA") - "Dividend payout ratio: KO vs KDP/PEP/KHC" -> compare_companies("KO", custom_peers="KDP,PEP,KHC", metrics="dividend_payout_ratio,dividend_yield")

• 2026-10-17get_financialschangeddescription
  before

  Get multi-period financial statements: income statement, balance sheet, and cash flow in one call. Returns quantitative historical data with key metrics and trends. Default: all 3 statements, quarterly, 2 years. For qualitative analysis (risks, accounting quality, management tone), use get_filing_index (signal map) then get_filing_section to read the text. Use Cases: - "Show me AAPL's financials" -> all statements - "MSFT revenue trend 5 years" -> period="annual", years=5 - "Is Tesla's debt increasing?" -> statements=["balance"] - "As of a past date / point-in-time" -> get_financials("MSFT", vantage_date="2024-04-30") Each period cites the SEC filing that reported it (accession + filed date in a footnote; resolvable EDGAR index handles in the `<raw_data>` block), so every figure is traceable to its source filing — except under vantage_date, where a later recast can sit under the vantage-era citation. **Exactness:** the markdown table ABBREVIATES (`$68.14M`) — it quantises to $10K above $1M and $10M above $1B, so it is not a tie-out surface. The `<raw_data>` block carries the exact stored value (`68135000`). Quote figures from `<raw_data>`, not the table, whenever the precise number matters. Responses capped at ~20K chars. If truncated, whole statements are dropped (not sliced) with a note — request fewer statements or reduce years. Note the cap also trims `<raw_data>` periods, so a truncated response can lose the exact channel for the dropped periods. Company-reported **Adjusted EBITDA** (issuer-specific add-backs) is NOT a computed metric here — read the issuer's own reconciliation via get_filing_section (earnings release / MD&A).

  after · 87% of words in common

  Get multi-period financial statements: income statement, balance sheet, and cash flow in one call. Returns quantitative historical data with key metrics and trends. Default: all 3 statements, quarterly, 2 years. For qualitative analysis (risks, accounting quality, management tone), use get_filing_index (signal map) then get_filing_section to read the text. Use Cases: - "Show me AAPL's financials" -> all statements - "MSFT revenue trend 5 years" -> period="annual", years=5 - "Is Tesla's debt increasing?" -> statements=["balance"] - "As of a past date / point-in-time" -> get_financials("MSFT", vantage_date="2024-04-30") Each period cites the SEC filing that reported it (accession + filed date in a footnote; resolvable EDGAR index handles in the `<raw_data>` block), so every figure is traceable to its source filing — except under vantage_date, where a later recast can sit under the vantage-era citation. **Exactness:** the markdown table ABBREVIATES (`$68.14M`) — it quantises to $10K above $1M and $10M above $1B, so it is not a tie-out surface. The `<raw_data>` block carries the exact stored value (`68135000`). Quote figures from `<raw_data>`, not the table, whenever the precise number matters. Responses capped at ~20K chars. If too large, the OLDEST periods are trimmed first (the same count for every statement, with a note); a whole statement is dropped only if one period of each still does not fit. Nothing is sliced, and `<raw_data>` carries exactly the periods shown — request fewer statements for more periods each. Company-reported **Adjusted EBITDA** (issuer-specific add-backs) is NOT a computed metric here — read the issuer's own reconciliation via get_filing_section (earnings release / MD&A).

• 2026-10-17get_stock_pricechangedinput schema
• 2026-10-16send_feedbackadded

  Call ONLY when the user asks to send feedback to MetricDuck. Pass the user's words in message; set source=user when the user wrote it, model when you summarised it. Sends the text to the MetricDuck team.

• 2026-10-15get_metric_historychangeddescription, input schema
  before

  Time series for one metric across fiscal periods. Returns newest-first rows labeled with the company's fiscal_year + fiscal_period — answer a period-specific question ("Q2 FY2025?") from those labels. The period_end calendar date is NOT the fiscal label, especially for non-December FYE companies (AAPL FY ends Sep; CRM FY ends Jan; ORCL FY ends May). Each row with an SEC accession is cited back to the source filing via the MetricDuck viewer. ⚠ CONSOLIDATED ONLY — there is no segment/geography/product breakdown here, and no parameter adds one: the metrics layer sums those axes away, so per-member values are never stored. For a BY-SEGMENT series use `get_xbrl_facts(ticker, search="<segment name> revenue", period_history=true)` (as-filed dimensional facts) or `get_filing_section(ticker, "table_segment_reporting")` (the schedule, 3 fiscal years per 10-K). Use Cases: - "What was AAPL's Q2 FY2025 gross margin?" -> get_metric_history("AAPL", "gross_margin") - "ROE last 5 years for MSFT" -> get_metric_history("MSFT", "roe", period_type="FY", window=5) - "As of a past date / point-in-time" -> get_metric_history("MSFT", "revenues", vantage_date="2024-04-30") Also serves NON-XBRL operating KPIs (LLM-extracted from earnings releases), almost all QUARTERLY — coverage varies by KPI. Besides the ids on `metric_id`: gross_booking_value, take_rate (marketplaces), revpar, occupancy_rate (lodging/REIT), passenger_load_factor, prasm, casm (airlines), oil_production, and more. Price-derived multiples here (pe_ratio, ev_ebitda, pb_ratio…) use the PERIOD-END close; for a price on a SPECIFIC date use get_stock_price. **Latest fiscal year during earnings season:** full-year results post in an earnings 8-K weeks before the 10-K that populates this FY series, so inside that gap the series ends a year early and this tool appends a pointer to the 8-K (get_filing_section "earnings_income_statement") — the year is not unavailable.

  after · 80% of words in common

  Time series for one metric across fiscal periods. Returns newest-first rows labeled with the company's fiscal_year + fiscal_period — answer a period-specific question ("Q2 FY2025?") from those labels. The period_end calendar date is NOT the fiscal label, especially for non-December FYE companies (AAPL FY ends Sep; CRM FY ends Jan; ORCL FY ends May). Each row with an SEC accession is cited back to the source filing via the MetricDuck viewer (under vantage_date, the vantage-era filing). ⚠ CONSOLIDATED ONLY — there is no segment/geography/product breakdown here, and no parameter adds one: the metrics layer sums those axes away, so per-member values are never stored. For a BY-SEGMENT series use `get_xbrl_facts(ticker, search="<segment name> revenue", period_history=true)` (as-filed dimensional facts) or `get_filing_section(ticker, "table_segment_reporting")` (the schedule, 3 fiscal years per 10-K). Use Cases: - "What was AAPL's Q2 FY2025 gross margin?" -> get_metric_history("AAPL", "gross_margin") - "ROE last 5 years for MSFT" -> get_metric_history("MSFT", "roe", period_type="FY", window=5) - "As of a past date / point-in-time" -> get_metric_history("MSFT", "revenues", vantage_date="2024-04-30") Issuer operating KPIs (subscribers, backlog, NIM, occupancy…) are not served here: read them in the company's release, `get_filing_section(ticker, "earnings_press_release")`. Price-derived multiples here (pe_ratio, ev_ebitda, pb_ratio…) use the PERIOD-END close; for a price on a SPECIFIC date use get_stock_price. **Latest fiscal year during earnings season:** full-year results post in an earnings 8-K weeks before the 10-K that populates this FY series, so inside that gap the series ends a year early and this tool appends a pointer to the 8-K (get_filing_section "earnings_income_statement") — the year is not unavailable.

• 2026-10-15get_financialschangeddescription, input schema
  before

  Get multi-period financial statements: income statement, balance sheet, and cash flow in one call. Returns quantitative historical data with key metrics and trends. Default: all 3 statements, quarterly, 2 years. For qualitative analysis (risks, accounting quality, management tone), use get_filing_index (signal map) then get_filing_section to read the text. Use Cases: - "Show me AAPL's financials" -> all statements - "MSFT revenue trend 5 years" -> period="annual", years=5 - "Is Tesla's debt increasing?" -> statements=["balance"] - "As of a past date / point-in-time" -> get_financials("MSFT", vantage_date="2024-04-30") Each period cites its original disclosing SEC filing (accession + filed date in a footnote; resolvable EDGAR index handles in the `<raw_data>` block), so every figure is traceable to its source filing. **Exactness:** the markdown table ABBREVIATES (`$68.14M`) — it quantises to $10K above $1M and $10M above $1B, so it is not a tie-out surface. The `<raw_data>` block carries the exact stored value (`68135000`). Quote figures from `<raw_data>`, not the table, whenever the precise number matters. Responses capped at ~20K chars. If truncated, whole statements are dropped (not sliced) with a note — request fewer statements or reduce years. Note the cap also trims `<raw_data>` periods, so a truncated response can lose the exact channel for the dropped periods. Company-reported **Adjusted EBITDA** (issuer-specific add-backs) is NOT a computed metric here — read the issuer's own reconciliation via get_filing_section (earnings release / MD&A).

  after · 94% of words in common

  Get multi-period financial statements: income statement, balance sheet, and cash flow in one call. Returns quantitative historical data with key metrics and trends. Default: all 3 statements, quarterly, 2 years. For qualitative analysis (risks, accounting quality, management tone), use get_filing_index (signal map) then get_filing_section to read the text. Use Cases: - "Show me AAPL's financials" -> all statements - "MSFT revenue trend 5 years" -> period="annual", years=5 - "Is Tesla's debt increasing?" -> statements=["balance"] - "As of a past date / point-in-time" -> get_financials("MSFT", vantage_date="2024-04-30") Each period cites the SEC filing that reported it (accession + filed date in a footnote; resolvable EDGAR index handles in the `<raw_data>` block), so every figure is traceable to its source filing — except under vantage_date, where a later recast can sit under the vantage-era citation. **Exactness:** the markdown table ABBREVIATES (`$68.14M`) — it quantises to $10K above $1M and $10M above $1B, so it is not a tie-out surface. The `<raw_data>` block carries the exact stored value (`68135000`). Quote figures from `<raw_data>`, not the table, whenever the precise number matters. Responses capped at ~20K chars. If truncated, whole statements are dropped (not sliced) with a note — request fewer statements or reduce years. Note the cap also trims `<raw_data>` periods, so a truncated response can lose the exact channel for the dropped periods. Company-reported **Adjusted EBITDA** (issuer-specific add-backs) is NOT a computed metric here — read the issuer's own reconciliation via get_filing_section (earnings release / MD&A).

• 2026-10-15get_company_overviewchangeddescription
  before

  Get comprehensive financial overview for a company in a single call. Includes: current price, valuation (P/E, P/B, EV multiples, PEG), profitability (revenue, margins, returns), cash flow (OCF, FCF, yields), balance sheet (debt, equity, ratios), capital allocation (buybacks, shares outstanding, shareholder yield), business segment + geographic revenue mix (latest 10-K, with YoY change), latest earnings insights, filing intelligence highlights, and company flags. Latest snapshot only — use get_financials for multi-year trends, get_xbrl_facts for multi-period segment history, get_filing_index for a signal map of the latest filing, compare_companies for peer benchmarking, get_stock_price for a historical/as-of-a-date close or a return between two dates (the price here is current only). Not point-in-time. For "as of <past date>" work use the tools that take `vantage_date` (get_financials, get_metric_history, get_filing_section, get_filing_index) and get_stock_price for a past close. Those bound which filings are visible, not restated values (get_financials and get_metric_history flag a LOOK-AHEAD); get_xbrl_facts with period_history=true gives figures as originally filed.

  after · 86% of words in common

  Get comprehensive financial overview for a company in a single call. Includes: current price, valuation (P/E, P/B, EV multiples, PEG), profitability (revenue, margins, returns), cash flow (OCF, FCF, yields), balance sheet (debt, equity, ratios), capital allocation (buybacks, shares outstanding, shareholder yield), business segment + geographic revenue mix (latest 10-K, with YoY change), latest earnings insights, filing intelligence highlights, and company flags. Latest snapshot only — use get_financials for multi-year trends, get_xbrl_facts for multi-period segment history, get_filing_index for a signal map of the latest filing, compare_companies for peer benchmarking, get_stock_price for a historical/as-of-a-date close or a return between two dates (the price here is current only). Not point-in-time. For "as of <past date>" work use the tools that take `vantage_date` (get_financials, get_metric_history, get_filing_section, get_filing_index) and get_stock_price for a past close. Those bound which filings are visible, not restated values: a later restatement or recast is served under the as-of citation, and the LOOK-AHEAD flag (get_financials, get_metric_history, get_filing_index) covers only a later amendment of the period's own filing. For figures as known then, pin get_xbrl_facts to the accession_number of the latest filing reporting the period (list_filings takes vantage_date); period_history=true gives figures as originally filed.

• 2026-10-11compare_companieschangeddescription, input schema
  before

  Compare a company against peers across ~70 curated fundamental metrics (TTM), with percentile rankings and relative strengths/weaknesses. Returns a side-by-side table covering valuation (P/E, P/B, EV/EBITDA, EV/Sales, FCF yield), profitability (gross/operating/net/EBITDA margins, ROE, ROA, ROIC), leverage & liquidity (debt/equity, net debt/EBITDA, interest coverage, current ratio), efficiency (asset/inventory turnover, DSO, cash conversion cycle), and capital returns (dividend yield, dividend payout ratio, buyback yield, shareholder yield). Sector-inapplicable metrics are omitted (e.g. gross margin / FCF leverage for banks). Pass 'metrics' to focus the table on specific metric_ids. This is a TTM cross-sectional snapshot — for a single company's value in a specific fiscal year/quarter use get_metric_history. Each company's row is dated: 'Data through' is its latest reported period, and valuation multiples are priced at the last close on/before that period end (period-end LOCF) — NOT today's price, and the dates can differ across peers by a quarter. For a multiple AS OF a specific date, or at the live price, or a CUSTOM definition (e.g. lease-adjusted EV), assemble it from get_stock_price (price leg) + get_metric_history primitives. peer_mode controls peer selection: - 'sector' (default): auto-selected from same sector + similar market cap - 'tags': auto-selected by business model similarity (tag Jaccard) — better for cross-sector comparisons Override with custom_peers for specific matchups. The number of custom_peers is capped by plan (Free: 3, Pro: 10); exceeding it returns the limit and the count you asked for, so retry with that many. Use Cases: - "Compare AAPL vs MSFT" -> compare_companies("AAPL", custom_peers="MSFT") - "How does NVDA stack up in its sector?" -> compare_companies("NVDA") - "Dividend payout ratio: KO vs KDP/PEP/KHC" -> compare_companies("KO", custom_peers="KDP,PEP,KHC", metrics="dividend_payout_ratio,dividend_yield")

  after · 95% of words in common

  Compare a company against peers across ~70 curated fundamental metrics (TTM by default; period_type FY or Q for each company's latest fiscal year or quarter), with percentile rankings and relative strengths/weaknesses. Returns a side-by-side table covering valuation (P/E, P/B, EV/EBITDA, EV/Sales, FCF yield), profitability (gross/operating/net/EBITDA margins, ROE, ROA, ROIC), leverage & liquidity (debt/equity, net debt/EBITDA, interest coverage, current ratio), efficiency (asset/inventory turnover, DSO, cash conversion cycle), and capital returns (dividend yield, dividend payout ratio, buyback yield, shareholder yield). Sector-inapplicable metrics are omitted (e.g. gross margin / FCF leverage for banks). Pass 'metrics' to focus the table on specific metric_ids. For one company's value in an older fiscal year/quarter use get_metric_history. Each company's row is dated: 'Data through' is its latest reported period, and valuation multiples are priced at the last close on/before that period end (period-end LOCF) — NOT today's price, and the dates can differ across peers by a quarter. For a multiple AS OF a specific date, or at the live price, or a CUSTOM definition (e.g. lease-adjusted EV), assemble it from get_stock_price (price leg) + get_metric_history primitives. peer_mode controls peer selection: - 'sector' (default): auto-selected from same sector + similar market cap - 'tags': auto-selected by business model similarity (tag Jaccard) — better for cross-sector comparisons Override with custom_peers for specific matchups. The number of custom_peers is capped by plan (Free: 3, Pro: 10); exceeding it returns the limit and the count you asked for, so retry with that many. Use Cases: - "Compare AAPL vs MSFT" -> compare_companies("AAPL", custom_peers="MSFT") - "How does NVDA stack up in its sector?" -> compare_companies("NVDA") - "Dividend payout ratio: KO vs KDP/PEP/KHC" -> compare_companies("KO", custom_peers="KDP,PEP,KHC", metrics="dividend_payout_ratio,dividend_yield")

Showing the latest 10. Full history: list_changes · trend: quality JSON.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.