MetricDuck

Retrieve IR earnings-PRESENTATION-DECK text — forward guidance, operational KPIs, and segment outlook that are ONLY in the company's investor-relations slide deck and NOT in the SEC 8-K/10-Q release text or XBRL. Reach for this when the answer is a forward-looking guidance range or an operational KPI that the structured tools miss: - get_metric_history / get_xbrl_facts return no series for a KPI or guidance figure - get_filing_section finds the 8-K earnings release but it lacks the guidance/KPI (decks are a separate exhibit/source) What lives here (not in XBRL/filing text): production or revenue guidance ranges, segment/division outlook, operational KPIs presented as slide charts (e.g., berth capacity %, Mboed production guidance, adjusted-EBITDA guidance). Use Cases: - "OXY Q3 2024 production guidance" -> get_ir_documents("OXY", fiscal_year=2024, fiscal_period="Q3", query="production guidance") - "NCLH berth capacity outlook" -> get_ir_documents("NCLH", fiscal_year=2021, fiscal_period="Q3", query="berth") - "KNTK adjusted EBITDA guidance range" -> get_ir_documents("KNTK", fiscal_year=2023, fiscal_period="Q3", query="EBITDA") Each deck returns its title, original IR url, a stable MetricDuck-hosted gcs_uri, and the matching slide text cited by page. Pass a `query` to land on the exact page; omit it for a bounded prefix of the latest deck. Resolve by ticker or cik; narrow with fiscal_year/fiscal_period.

get_ir_documents

Retrieve a company's IR event CALENDAR — UPCOMING and PAST investor-relations events (earnings calls, annual/shareholder meetings, broker conferences, investor days) with the materials attached to each (deck, webcast, press release, transcript). Reach for this to answer time/calendar questions the document catalog can't: - "When does {ticker} next report / hold its earnings call?" → the UPCOMING list (scheduled events) - "What IR events did {ticker} have this year?" / "was {ticker} at any conferences?" - "What materials are attached to {ticker}'s last earnings event?" Each event has: occurred_at (issuer-local datetime) + time_precision, event_type (verbatim/open vocab), the verbatim source title, and material chips — each material's `material_id` is the get_ir_documents doc_id (a POINTER; read the content with get_ir_documents, not here). Coverage is honest: if a company hasn't been harvested yet, that is stated — an empty result does NOT mean the company has no IR events. `last_checked_at` stamps the calendar's as-of time (events announced since are not shown). For a deck's slide TEXT → get_ir_documents. For what management SAID on an earnings call (guidance/tone by quarter) → compare_earnings_calls.

get_company_events

Browse Sources inventory and the section catalog for a single company. Covers SEC filings: 10-K, 10-Q, 8-K, DEF 14A, plus 20-F / 40-F / 6-K for foreign private issuers. **Scope:** filings-metadata utility. Returns filing list (form type, dates, accession numbers) plus per-section details (word count, chunk count, tables) for 10-K/10-Q/DEF 14A; 8-K returns filing metadata only. Default: last 2 years. Use `fiscal_year` + `fiscal_period` to pin a single historical filing in one call. **For signal triage and "what matters" in a filing, use `get_filing_index` instead.** Use `list_filings` only when: - You need an accession_number for a specific historical filing (before `get_xbrl_facts` or `get_filing_section`) - You need to pin a specific fiscal year/period (e.g., FY2020 Q3) - You need the full section inventory with sizes to plan pagination - You need to confirm whether a specific filing exists Sister Sources (non-SEC): - Earnings call transcripts → `compare_earnings_calls` (cross-quarter view) - IR press releases / events → `screen_filing_signals` with signal_type="ir_press_release" **Delisted / acquired issuers**: pass `cik` (10-digit, zero-padded) instead of (or alongside) `ticker` and set `include_delisted=true`. SEC's ticker registry excludes delisted issuers, so `ticker`-only calls 404 even when filings exist in MetricDuck. Examples: SAVE Spirit Airlines (`cik="0001498710"`), RDFN Redfin (`cik="0001382821"`), ATVI Activision (`cik="0000718877"`). Data horizon: 2013+. Responses capped at ~20K chars; narrow via `form_type`, `fiscal_year`, or reduce `years`.

list_filings

Time series for one metric across fiscal periods. Returns newest-first rows with fiscal_year + fiscal_period labels — AUTHORITATIVE for period-specific questions ("Q2 FY2025?"). 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. 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) - "NVDA TTM revenue trend" -> get_metric_history("NVDA", "revenues", period_type="TTM") - "ABNB gross booking value trend" -> get_metric_history("ABNB", "gross_booking_value") (operating KPI; quarterly or FY) - "Net interest margin for a bank" -> get_metric_history("<bank>", "net_interest_margin") - "As of a past date / point-in-time" -> get_metric_history("MSFT", "revenues", vantage_date="2024-04-30") (series as known from filings published on/before that date) Common XBRL metric_ids: gross_margin, oper_margin, net_margin, ebitda_margin, roe, roa, roic, pe_ratio, ev_ebitda, ev_sales, fcf_yield, pb_ratio, current_ratio, debt_to_equity, interest_coverage, revenues, net_income, ebitda, fcf, net_cf_ops, capex, dividends_per_share, dividends_paid, dividend_yield, dividend_payout_ratio, fcf_payout_ratio, dividend_coverage. Also serves NON-XBRL operating KPIs (LLM-extracted from 10-K/10-Q MD&A + earnings releases), available QUARTERLY and ANNUAL (FY) — coverage varies by KPI. This set spans banking (net_interest_margin, common_equity_tier_1_capital_ratio, return_on_average_assets/equity), insurance (combined_ratio), SaaS (arr, remaining_performance_obligations), retail/marketplace (store_count, same_store_sales, gross_booking_value, take_rate), lodging/REIT (revpar, occupancy_rate, average_daily_rate), airlines (passenger_load_factor, prasm, casm), energy (oil_production), workforce (headcount), and more — full data-derived (non-exhaustive) list: net_interest_margin, return_on_average_assets, return_on_average_equity, nonperforming_assets_to_total_assets, nonperforming_loans_to_total_loans, allowance_for_credit_losses_to_total_loans, loan_to_deposit_ratio, net_charge_offs_to_average_loans, common_equity_tier_1_capital_ratio, tier_1_leverage_ratio, tier_1_capital_ratio, total_capital_ratio, return_on_average_tangible_common_equity, net_leverage_ratio, nonperforming_loan_ratio, liquidity_coverage_ratio, net_stable_funding_ratio, combined_ratio, loss_ratio, expense_ratio, policies_in_force, arr, recurring_revenue, remaining_performance_obligations, organic_revenue_growth, cancellation_rate, subscribers, arpu, store_count, same_store_sales, average_order_value, active_customers, customers, active_buyers, orders, bookings, backlog, gross_booking_value, nights_and_seats_booked, monthly_active_platform_consumers, trips, take_rate, occupancy_rate, average_daily_rate, revpar, weighted_average_remaining_lease_term, assets_under_management, passenger_load_factor, available_seat_miles, revenue_passenger_miles, passenger_mile_yield, prasm, trasm, casm, casm_ex, oil_production, natural_gas_production, book_to_bill_ratio, wafer_shipments, production_capacity, headcount, full_time_equivalent_employees, cash_runway. If a KPI you need isn't listed, just try its canonical name; only if it's truly absent does it live solely in filing text — then reach it via get_filing_section(ticker, "mda_results_operations", query=…) or compare_earnings_calls(ticker). Metric_id matching is strict (lowercase, exact spelling). Financial-sector tickers (banks, insurers) often NULL on COGS-based metrics (gross_margin, gross_profit) — use sector-appropriate alternatives (e.g. net_interest_margin, combined_ratio) where available. 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. To assemble a CUSTOM multiple (e.g. EV including operating leases) combine get_stock_price (price leg) with get_metric_history primitives: oper_lease_liabs, ttl_debt, cash_st_invs, ttl_equity, shares_basic. **Latest fiscal year during earnings season:** full-year results post in an earnings 8-K weeks before the 10-K, which is what populates this structured FY series. If you query the latest FY inside that gap, the series ends one year early — this tool then appends a pointer to the earnings 8-K; follow it (get_filing_section "earnings_income_statement") rather than concluding the year is unavailable. Adjacent tools: get_company_overview for a single-period snapshot across many metrics; get_financials for full statements (all line items) across multiple periods; get_stock_price for daily share prices and period returns.

get_metric_history

The DERIVATION of one COMPUTED metric — its human formula + immediate inputs (each value + source), one level at a time. The audit / verify affordance for derived figures (margins, ratios, ROIC, FCF, adj-EBITDA): call it ONLY when the query asks **how a metric is computed**, **which definition** MetricDuck used, or to **verify / audit** the derivation — NOT to get the value itself (use get_metric_history / get_company_overview for that). Drillable (lazy, one level per call): - a `derived` input points to its OWN derivation — call get_metric_lineage(ticker, that_symbol) to go deeper. - a `base` input is an as-filed XBRL fact — open its filing handle, or get_xbrl_facts(ticker, search="<symbol>") to land on the exact fact. Use Cases: - "How is AAPL's net_margin calculated?" -> get_metric_lineage("AAPL", "net_margin") - "Which ROIC definition does this use?" -> get_metric_lineage("AAPL", "roic") - "Audit / verify gross_margin for Q2 FY2025" -> get_metric_lineage("AAPL", "gross_margin", fiscal_year=2025, fiscal_period="Q2") Computed metrics only — a base as-filed figure has no derivation (the tool says so and points to get_xbrl_facts).

get_metric_lineage

Raw XBRL facts from SEC filings — use only when `get_financials` cannot answer the question. **Scope:** escape-hatch for dimensional / industry-specific / as-filed numbers. ~3,000 facts per filing with dimensional breakdowns (segment, geography, product line). Search by human-readable label (not XBRL concept names). **First try `get_financials`** — it covers the 323+ standard metrics (revenue, margins, EPS, FCF, ROIC, leverage, etc.) across TTM/FY/Q + YOY/CAGR dimensions for all 5,500+ companies. It is faster, cheaper, and more portable across tickers. **Use `get_xbrl_facts` only when:** - You need a segment / geographic / product-line breakdown that `get_financials` aggregates away — available only for concepts the filer XBRL-tags dimensionally (usually revenue + segment profit / Adjusted EBITDA). Segment-level **costs / operating expenses** are frequently NOT tagged — but a single segment's total operating expense = its **Revenue − Adjusted EBITDA** (both usually ARE tagged dimensionally), so search both members and subtract. Finer per-segment cost DETAIL (e.g. programming vs other) lives only in the MD&A — `get_filing_section(section_id="mda_results_operations", query="<segment> total costs and expenses adjusted ebitda")`. - You need **revenue concentration / share** by customer, channel, distributor, geography, or product — the as-filed `ConcentrationRiskPercentage` facts (e.g. "what % of revenue from channel partners / a distributor / a region"). Deterministic and present even when the filing prose only describes the relationship qualitatively. Search `concentration`. - You need an industry-specific metric not in the standard catalog (e.g., `medical cost ratio` for a health insurer, `reserve replacement ratio` for an oil & gas name) - You need to verify a specific number from filing text against the as-filed XBRL value - You need a historical fiscal year not returned by `get_financials` (pass `fiscal_year`) - You need a cash-flow / income **line across periods to de-cumulate a standalone quarter** — the as-filed cash-flow statement is cumulative YTD (a Q2 10-Q reports the 6-month figure). Set `period_history: true` to get the concept's full series (quarter / 6-mo / 9-mo / FY) across filings in one call, then subtract the prior YTD sharing the same start date (Q2 standalone = 6-month YTD − Q1 3-month). **Sign:** values are the as-filed positive MAGNITUDES. Facts the filing presents NEGATIVE — a cash OUTFLOW (`PaymentsTo…`, `IncreaseDecreaseIn…`, capex, inventory build, "Other, net") or a contra-asset (accumulated depreciation) — are flagged `(filed −)` in the table and carry `is_negated: true` in the `<raw_data>` envelope; apply that sign when interpreting direction. For ready-signed cash-flow / income lines, `get_financials` applies statement signs for you. **Exactness:** the markdown rounds for readability; the `<raw_data>` block carries each fact's EXACT value + `decimals` (the as-filed precision floor: −3 = thousands, −6 = millions) + a stable `mdck` handle + two ways to see the fact in its filing: `handle.edgar` (SEC EDGAR — the independent primary source) and `handle.viewer` (the MetricDuck viewer, which opens the filing with the fact highlighted; auto-falls back to EDGAR with a plain scroll when the filing isn't cached in MD). **Share counts (pick the right basis):** the **dei** `EntityCommonStockSharesOutstanding` (shown as "cover-page / current") is the most-current shares outstanding, as of the filing/cover date — use it for **market cap, equity value, and "shares outstanding from the cover page"**. The **us-gaap** `CommonStockSharesOutstanding` is the **balance-sheet period-end** count (an earlier date); `WeightedAverageNumberOf…SharesOutstanding` is the **per-period average for EPS**. These can differ a few % for buyback-heavy / recently-issuing filers — match the as-of date in the Period column to your task. Searching: comma-separated terms OR-match (e.g., `revenue,product`). Responses are capped at ~20K chars — over the cap, whole facts are paged out of BOTH the table and the `<raw_data>` block together (the JSON stays valid) with an explicit `facts_omitted` count; narrow the search or lower `limit` for the rest.

get_xbrl_facts

Read a specific section from an SEC Source (10-K, 10-Q, 8-K earnings, 8-K events, or DEF 14A proxy). **Two modes:** 1. **Section mode (default)** — pass section_id for full paginated text (up to 10 chunks per page). 2. **Outline mode** — OMIT section_id and pass accession_number to receive the filing's section TOC with ~120-char content previews per section. Use this when drilling into an unfamiliar Source (multi-exhibit 8-K, DEF 14A, FPI 6-K) to pick the right section by content rather than guessing from section_id. Use list_filings first to discover accession numbers. In section mode, omitting accession_number returns the latest filing's section. The section_id field description (below) enumerates valid IDs by category. Use Cases: - "Apple risk factors" -> get_filing_section("AAPL", "risk_factors") - "Customer concentration in NVDA" -> get_filing_section("NVDA", "risk_factors", query="customer concentration") - "Workforce / headcount / employees by geography" -> get_filing_section("MSFT", "business_description", query="human capital") (Human Capital Resources lives in Item 1, not a separate section) - "M&A terms" -> get_filing_section("CVX", "item_1_01_material_agreement", form_type="8-K") - "As of a past date / point-in-time" -> get_filing_section("MSFT", "business_description", vantage_date="2025-04-07") (serves the latest 10-K filed on/before that date — use this for time-anchored questions instead of assuming the newest filing; or pin an exact report via accession_number from list_filings) - "Multi-exhibit 8-K" -> get_filing_section(ticker, accession_number="...") (outline mode) → pick exhibit → get_filing_section(ticker, section_id="item_7_01_exhibit_99_02") Sister Sources (non-SEC): - Earnings call transcripts → `compare_earnings_calls` (cross-quarter view) or list_filings + section_id="transcript_prepared_remarks" - IR press releases / events → `screen_filing_signals` with signal_type="ir_press_release" - Forward guidance / operational KPIs / segment outlook in the earnings PRESENTATION DECK (not in the SEC filing or XBRL) → `get_ir_documents(ticker, fiscal_year, fiscal_period, query=…)` - Raw XBRL dimensional facts → `get_xbrl_facts` - Year-over-year risk-factor change detection ("what's new/changed vs last year's `risk_factors`") → `screen_filing_signals(signals=["has_new_risks"], ticker=…)` — a computed vs-prior-filing signal, cheaper and more reliable than reading two filings and diffing the prose yourself - A figure ABSENT from the section you expected → `search_sec_filings(company=<ticker/CIK>, query="exact phrase")` locates which section of which filing carries it (per-section drill-in pointers) — absence from one section does not mean the filing lacks it **Delisted / acquired issuers**: pass `cik` (10-digit, zero-padded) instead of `ticker` and set `include_delisted=true`. Examples: SAVE Spirit Airlines (`cik="0001498710"`), RDFN Redfin (`cik="0001382821"`). Responses capped at ~20K chars. Use offset for pagination or query to narrow results.

get_filing_section

Discover recent SEC filings landed since a watermark — single call, universe-wide, optional portfolio filter. **Use this when:** building event-driven agent workflows (Routines, alerts, daily portfolio checks). The right primitive when the question is "what new filings have landed?" rather than "what filings does this one company have?". **Returns:** flat list of {ticker, accession, filed_at, form_type, form_subtype}, newest filing date first and **largest issuers first within a date** — so `limit=15` during earnings week surfaces the banks and mega-caps that filed, not the alphabetically-first micro-caps. `form_subtype` is computed from the filing's section inventory: '8-K-earnings' (has any earnings_* section), '8-K-transcript' (has any transcript_* section), '8-K-event' (has any item_* section), '8-K-other' (8-K with none of the above), or null for non-8-K forms. **Cost:** ~one call regardless of portfolio size — vs O(N) calls if you fan out per-ticker via `list_filings`. **Composition:** for each row in the result, drill in via `get_filing_section(ticker, accession_number=...)` (omit `section_id` for the filing's section outline) to see what is in that specific filing, then `get_filing_section` with a `section_id` for narrative content. **Use `list_filings` instead when:** you need ALL filings for ONE company (paginate by year). `list_recent_filings` is the cross-company / event-discovery primitive; `list_filings` is the per-company catalog.

list_recent_filings

Screen 5,500+ US companies by financial metrics. Find stocks matching quantitative criteria. Metric IDs (canonical names from filing_metrics): - Valuation: pe_ratio, pb_ratio, ev_ebitda, fcf_yield, market_cap, ev - Profitability: gross_margin, oper_margin, net_margin, ebitda_margin, roe, roa, roic - Cash Flow: fcf, net_cf_ops, cash_conversion - Balance Sheet: debt_to_equity, current_ratio, ttl_debt, ttl_equity, cash_st_invs - Size: revenues, net_income, ebitda, gross_profit Growth screening: use period_type on any base metric: - Revenue growth YoY: metric_id="revenues", period_type="ttm.yoy" - 3-year revenue CAGR: metric_id="revenues", period_type="ttm.cagr3" - Earnings growth: metric_id="net_income", period_type="ttm.yoy" Period types: ttm (default), q, fy, ss (balance sheet snapshot), ttm.yoy, ttm.cagr3, ttm.cagr5 Sectors: TECH, FIN, HEALTH, CONS_STAPLES, CONS_DISC, IND, ENERGY, UTIL, RE, MAT, COMM Operators: gt (>), gte (>=), lt (<), lte (<=), eq (=), between Tag filtering (required_tags / excluded_tags): filter by business model classification. Requires companies to be classified — unclassified companies are excluded from tag-filtered results. Note: For P/E screening, negative P/E means losses. Add a gt(0) filter to exclude loss-making companies. Note: ROIC values are decimals (0.15 = 15%). Margins and returns are also decimals. Use Cases: - "High ROIC tech stocks" -> filters=[{metric_id:"roic", operator:"gt", value:0.15}], sectors=["TECH"] - "Undervalued profitable industrials" -> filters=[{metric_id:"pe_ratio", operator:"lt", value:15}, {metric_id:"pe_ratio", operator:"gt", value:0}], sectors=["IND"] - "Revenue growing >10% YoY" -> filters=[{metric_id:"revenues", operator:"gt", value:0.10, period_type:"ttm.yoy"}] - "AI infrastructure companies not exposed to China supply chain" -> required_tags=["ai_ml_infrastructure"], excluded_tags=["china_supply_chain_heavy"] - "Profitable subscription businesses" -> filters=[{metric_id:"net_margin", operator:"gt", value:0.10}], required_tags=["subscription_recurring"] To screen by filing SIGNALS (tone, covenant risk, material weakness, etc.), use screen_filing_signals — a universe-correct cross-company signal screen — then intersect with a metric screen here. Responses capped at ~20K chars. If truncated, reduce limit or add stricter filters.

screen_companies

Screen companies by signals across all source types — filings, earnings, transcripts, IR events. This is NOT metric screening (use screen_companies for P/E, ROIC, etc.). Screens by verifiable facts, not LLM-generated scores. Available signals: Filing intelligence (from 10-K/10-Q): - tone_cautious: Management tone is cautious/defensive - customer_concentration_high: Customer concentration > 20% or elevated risk - covenant_risk: Covenant tight, waiver obtained, or violation - debt_maturity_near: Significant debt maturing within 12 months - dividend_coverage_weak: Dividend coverage below operating cash flow - sbc_unhedged: Stock comp exceeds buybacks (net dilution) - has_fuel_sensitivity: Fuel cost sensitivity quantified in MD&A - mda_has_scale_claims: ≥3 quantified operational scale claims extracted from MD&A narrative (e.g. renewal rates, member counts, comp sales) Earnings releases (8-K Item 2.02 and 6-K Ex 99.1, from earnings press releases): - earnings_revenue_grew: Revenue grew year-over-year - earnings_revenue_declined: Revenue declined year-over-year - earnings_margin_expanded: Operating or gross margin expanded vs prior year - earnings_margin_contracted: Operating or gross margin contracted vs prior year - earnings_guidance_raised_8k: Forward guidance raised in earnings release - earnings_guidance_lowered_8k: Forward guidance lowered in earnings release - earnings_has_special_items: Non-recurring charges or special items disclosed - earnings_accrual_concerning: Accrual quality weak or concerning (cash vs earnings divergence) - earnings_has_capital_return: Shareholder capital returned (buybacks and/or dividends) Transcript (from earnings call Q&A): - transcript_has_guidance: Specific guidance given on earnings call - transcript_has_prepared_remarks: Prepared remarks available (true for all transcript sources) - transcript_has_analyst_questions: Analyst Q&A captured with topics + firms - transcript_guidance_raised: ≥1 guidance item raised vs prior quarter (from transcript) - transcript_guidance_lowered: ≥1 guidance item lowered vs prior quarter (from transcript) - transcript_has_revenue_decompositions: Segment-level revenue decomposed into quantified drivers (volume / price / mix / FX / M&A) on call - transcript_qa_concerns_retained: ≥2 analysts left with concerns retained after Q&A - transcript_qa_forward_committed: ≥2 executive responses with forward-looking commitments on call (count-based; transcript_has_forward_commits exposes the underlying instances) IR events (from company press releases): - ir_partnership: Strategic partnerships announced DEF 14A proxy statements (from compensation disclosures): - def14a_peer_group: Compensation peer group disclosed (with company names) - def14a_ceo_pay_ratio: CEO pay ratio disclosed Use Cases: - "Which tech companies have cautious management?" -> signals=["tone_cautious"], sectors=["TECH"] - "Does NVDA have any tone_shifted recently?" -> ticker="NVDA", signals=["tone_shifted"], recency_days=30 - "Did AAPL disclose new risk factors vs last year's 10-K?" (year-over-year risk surveillance) -> ticker="AAPL", signals=["has_new_risks"] — prefer this over reading risk_factors for two periods via get_filing_section and diffing the prose by hand - "Companies that gave specific guidance on calls?" -> signals=["transcript_has_guidance"] - "Which companies announced strategic partnerships or M&A deals?" -> signals=["ir_partnership"] Cross-filing composition (Brief 35 — Pattern 4): `ir_partnership` matches on M&A / partnership 8-K anchors (Item 1.01) carry a `companion_accessions: string[]` field in their payload value when the announcement is split across an anchor + same-day companion 8-K (7.01 Reg FD + Ex 99 press release / 8.01 other events). To read the full announcement narrative — CEO quotes, deal terms, investor-presentation text living in the companion — pass those accession numbers to `get_filing_section({..., section_id:"item_1_01_material_agreement", include_companions:true, companion_accessions:[...]})`. Empty list means no companion exists or the producer hasn't backfilled it (acceptable; anchor-only flow still works).

screen_filing_signals

Resolve a company name or ticker to the exact ticker symbol via fuzzy name/ticker match. **Scope:** exact-entity lookup only. Handles partial names ("micro" -> MSFT), typos, and ticker variations. Returns ticker, full name, CIK, SIC, filer type (domestic / foreign private issuer / fund — i.e. which form family to expect), fiscal year-end, and a primary-source SEC EDGAR entity-page link (verify the resolution + see the company's full filing history) for each match. **Use this when:** you have a specific company name or ambiguous ticker and need to confirm the exact ticker before calling other tools. **Delisted / renamed / acquired companies** are resolvable by current OR former name (e.g. "American Software" → Logility, "Chase Manhattan" → JPM). They are returned ranked below active matches, flagged `[delisted]`, with their CIK. They have no current ticker — pass the returned `cik` to downstream tools (every company tool accepts a CIK in place of a ticker). **Input tip:** queries matching the pattern of 2-5 uppercase letters are auto-extracted as a ticker. If you pass an all-caps company name (e.g., "AMCOR") that is NOT a ticker, the lookup may miss — pass "Amcor" with normal casing to force name-search behavior. On miss, this tool returns suggested near-matches when possible. **Do NOT use this for concept/theme/industry discovery** (e.g., "gold miners", "LNG exposure", "companies mentioning tariffs"). This tool matches on company-name text only — it cannot surface companies by what they do. For concept discovery, use `search_sec_filings` (full-text search across filings) or `screen_companies` (metric + sector filters). **Coverage boundary:** MetricDuck is **SEC-EDGAR only**. This tool is the authoritative coverage check. A no-match on a **non-US local-exchange symbol** (e.g. `3087.T`, `LSE:HSBA`, `7203:JP`) is a coverage boundary, not a lookup miss — the tool says so explicitly and you should treat it as **terminal** (don't retry ticker variations). Foreign issuers that file a US 20-F/40-F (HSBC, Toyota, Novo Nordisk…) ARE covered — reach them by **company name**, not their local symbol.

search_companies

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 (e.g. an announcement landing on a weekend): pass start_date=<date>; the FIRST row 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. - A single specific date: pass start_date=<date> (omit end_date) — returns a short forward window whose first row is your on/after price. Use Cases: - "AAPL close on 2025-07-28" -> get_stock_price("AAPL", start_date="2025-07-28") (first row = that day or next open day) - "DKNG total return 2025-01-02 → 2026-02-27" -> TWO calls: get_stock_price("DKNG", start_date="2025-01-02") and get_stock_price("DKNG", end_date="2026-02-27"); take each first/last close and compute the return (cheaper than one 14-month window) - "SUI 1/14/30 calendar days after an 8-K date" -> get_stock_price("SUI", start_date="<announce>", end_date="<announce + ~32d>"), then pick the first row on/after announce, +1, +14, +30 - "Latest price" -> get_stock_price("AAPL") When the window spans ≥2 trading days, the response also reports the first/last close and the period return on BOTH close (literal point-to-point) and adj_close (split/dividend-adjusted — the true economic return; the two diverge across a split or dividend). 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. For period-end valuation multiples (P/E, EV/EBITDA, P/B) use get_metric_history; to assemble a CUSTOM multiple (e.g. lease-adjusted EV) combine this price with get_metric_history("ticker","oper_lease_liabs" / "ttl_debt" / "cash_st_invs" / "ttl_equity" / "shares_basic").

get_stock_price