Data Denver

 ⟨8 unchanged words⟩ as ask_pipeworx — picks the right tool from 67,997115 across 18391872 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 18391872 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ , routes each to the right one of 67,997115 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

Realizable-vs-theoretical edge check against live CLOB order-book depth.depth — AND Polymarket's own taker fee, which is never zero and is folded in rather than left for you to add (fleet #3446: r/PredictionsMarkets flagged a "clean" fill that quietly omitted it as optimistic in the direction that loses money). REQUIRES one of `market` (single-market mode) or  ⟨33 unchanged words⟩  top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, andverdict (clean|degraded|cannot_fill), fee_schedule ({category, taker_rate, exponent, maker_rebate_rate, fees_enabled, basis} — read off THIS market, never assumed free), fee_usd/fee_pp at the actual VWAP fill, breakeven_win_rate_taker (the win probability your side needs just to cover price + fee — ~51.8% on a verdict50c crypto taker fill, not 50%), breakeven_win_rate_maker (clean|degraded|cannot_fillno fee charged to makers — any rebate is in fee_schedule.maker_rebate_rate)., and all_in_cost_pp = slippage_pp + fee_pp. BASKET: pass an event slug/URL + side ( ⟨36 unchanged words⟩ (top-of-book vs VWAP across all legs), capture_ratio, and profit_usd at— executedboth sizeNET of every leg's own Polymarket taker fee (capture_ratio_gross/profit_usd_gross keep the pre-fee figures; per_leg[].fee_usd itemizes each leg, summed as fees_usd_total), per-leg fill detail, thin_legs[], max_clean_notional_usd, and ⟨47 unchanged words⟩ dominant loss mode in real arb-bot P&L). FEES ARE NOT MODELLED HERE: vwap_fill_price/profit_usd are GROSS of Polymarket's own taker fee (rate 0.04-0.07 by category — see polymarket_edges/fees.ts), on top of which this tool prices depth-crossing cost; a thin-marginAdverse fillselection thatwhile looksworking cleanresting hereorders canis still be net-negative after thenot fee.modeled.

Extract the settlement clause of a single Polymarket (.com or .us) or Kalshi market: who publishes the settling number (source), the clock time + timezone it is taken at (falling back to the market TITLE when the clause itself says "the time range specified in the title" — e.g. Polymarket's 15-minute Chainlink TWAP family), the precision of the computation (e.g. "1-minute candle close" vs "60-second trailing average" vs "twap_60s_lookback"/"twap_30s_lookback" vs "election outcome"), comparison_basis — what is compared to what (end_average_vs_start_average | close_vs_open; orthogonal to precision, since venues can share this comparison shape while computing each endpoint differently), the evidence standard (official_source | consensus_reporting | any_credible_report ⟨15 unchanged words⟩ . Parses Polymarket's `description` field (fetched via polymarket_market, or via polymarket_us_search for the .us venue) or Kalshi's `rules_primary` + `rules_secondary` fields (fetched ⟨21 unchanged words⟩ a guess. Pass `market` as a Polymarket slug/URL (either venue) or a Kalshi market ticker (e.g. "KXBTCD-26SEP1317-T66999.99" ⟨44 unchanged words⟩  that look alike can settle on different sources (Polymarket.com's Chainlink TWAP stream vs Kalshi/Polymarket US's CF Benchmarks BRTI), at different times, or with a different precisionlookback window — this tool is how you check. Pair ⟨27 unchanged words⟩ 

 ⟨9 unchanged words⟩ properties":{"market":{"description":"Polymarket (.com or .us) market slug or URL, OR a Kalshi market ⟨19 unchanged words⟩ ":"Which venue to fetch the market from. \"polymarket\" is the offshore venue (polymarket.com); \"polymarket-us\" is the separate, CFTC-regulated polymarket.us venue, matched by slug via its own search (no exact-slug lookup exists upstream).","enum":["polymarket","kalshi","polymarket-us"],"type":"string"}},"required" ⟨4 unchanged words⟩ 

 ⟨10 unchanged words⟩ of `a` and `b`; either can be Polymarket .com, Polymarket US, or Kalshi) — runs resolution_audit on both sides and compares source, settle time, precision, comparison_basis, and evidence standard. Returns `equivalent`: "true" only ⟨52 unchanged words⟩  at 5pm EDT — SAME asset, DIFFERENT contractcontract; or ["source","precision"] for Polymarket.com's Chainlink 15-minute TWAP clause (precision "twap_60s_lookback") against Kalshi's 15-minute KXBTC15M clause (precision "60-second trailing average" off CF Benchmarks' BRTI) — different source and a different lookback mechanism, even though BOTH compare an end-of-window average to a start-of-window average, so comparison_basis is EQUAL there and correctly NOT in differing_fields — verified live 2026-10-22, fleet #3447); "unclear" when one or both sides  ⟨14 unchanged words⟩ — read raw_clause yourself in that case). comparison_basis is flagged as differing whenever both sides resolved one and they disagree, independent of whether source/precision also matched. Only flags a fieldsource/evidence_standard as differing when BOTH sides gave a SPECIFIC ⟨66 unchanged words⟩ 

 ⟨22 unchanged words⟩ venue":{"enum":["polymarket","kalshi","polymarket-us"],"type":"string"}},"required": ⟨14 unchanged words⟩ "venue":{"enum":["polymarket","kalshi","polymarket-us"],"type":"string"}},"required" ⟨9 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,876997 across 18111839 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨175 unchanged words⟩  FY2026 and Apple's ending 2025-09-27 is FY2025. Attributes in v1: revenue, net_income, cash.cash, gross_profit, operating_income, eps_diluted, capex, operating_cash_flow, long_term_debt, shares_outstanding (the dei COVER-PAGE share count, so its period end is the cover date, after the quarter closed — that is the most current count the filing carries). Units are not all USD: shares_outstanding is in `shares` with currency null, eps_diluted in `USD/shares`. A discrete quarter the filer never filed — every Q4, and Q2/Q3 of cash-flow lines, which are filed year-to-date — is DERIVED as YTD(q) minus YTD(q-1) and comes back with `reported: false`, the subtraction named in `derivation` (fy_minus_9m / ytd_9m_minus_6m / ytd_6m_minus_3m) and both legs with their filings in `derived_from`; test `reported` if you will only accept a figure lifted from a filing. Per-share and balance-sheet figures are NEVER derived. Every non-answer is a named status — `unavailable` ⟨92 unchanged words⟩ 

 ⟨6 unchanged words⟩ {"fiscal_year":2023,"type":"annual"}},{"attribute":"shares_outstanding","company":"TSLA","period":{"fiscal_quarter":2,"fiscal_year":2026,"type":"quarterly"}},{"attribute":"capex","company":"TSLA","period":{"fiscal_quarter":2,"fiscal_year":2026,"type":"quarterly"}},{"attribute":"net_income","company":"TSLA","period":{"fiscal_quarter":4,"fiscal_year":2025,"type":"quarterly"}}],"properties":{"as_of":{"description": ⟨41 unchanged words⟩ = cash and cash equivalents at the period end.end; \"gross_profit\"; \"operating_income\"; \"eps_diluted\" (diluted EPS, unit USD/shares, never derived or summed); \"capex\" (cash paid for PP&E); \"operating_cash_flow\" (net cash from operating activities); \"long_term_debt\" (the noncurrent balance-sheet line where the filer tags it, else total long-term debt — `fact.measure` says which); \"shares_outstanding\" (dei cover-page common shares, unit \"shares\", as of the COVER DATE rather than the period end).","enum":["revenue","net_income","cash","gross_profit","operating_income","eps_diluted","capex","operating_cash_flow","long_term_debt","shares_outstanding"],"type":"string"},"basis": ⟨307 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 18111839 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,876997 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

 ⟨104 unchanged words⟩ //edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATESTthe 10-Klatest RevenuesANNUAL +Revenues, NetIncomeLoss +, Cash, sorteddiluted EPS, capex and operating cash flow, each with its period_end, DESCSEC form and the accession of the filing it came from — plus EntityCommonStockSharesOutstanding, which is the newest COVER-PAGE share count the filer has published rather than an annual one, so its period_end is a cover date after the quarter closed and it is the right per-share denominator; a filer tagging a fallback concept appears under the name of that tag instead, e.g. PaymentsToAcquireProductiveAssets instead of PaymentsToAcquirePropertyPlantAndEquipment); patents (USPTO PatentsView API sunset May  ⟨192 unchanged words⟩ 

Beta version of ask_pipeworx: identical universal router (same 6,626876 tools, same arguments, same response shape)  ⟨68 unchanged words⟩ 

 ⟨27 unchanged words⟩  for question.","type":"string"},"packs":{"description":"OPTIONAL. Restrict routing to these pack slugs (e.g. [\"sec-form-d\",\"sec-13f\"]) — the router then picks only from tools in those packs. Omit for the default full-catalog routing. Slugs come from list_packs / search_packs / https://pipeworx.io/directory; unlisted or unknown slugs are ignored and named in _meta.pack_scope.ignored, and if none of them resolves the question is routed across the whole catalog with _meta.pack_scope.full_catalog:true (never an empty answer).","items":{"type":"string"},"type":"array"},"prompt":{"description":"Alias for question.", ⟨48 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,626876 across 17391811 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨26 unchanged words⟩  for question.","type":"string"},"prefer_tool":{"description":"Run this exact tool instead of letting the router choose — use a name from a previous answer's alternatives[]. Arguments are still filled from your question. Unknown names are refused, never guessed.","type":"string"},"prompt":{"description":"Alias for question.", ⟨46 unchanged words⟩ 

 ⟨259 unchanged words⟩ no accession behind it). Source: SEC EDGAR, XBRL companyconceptfinancial facts, one publisher read once — see `corroboration`.  ⟨11 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 17391811 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,626876 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

 ⟨3 unchanged words⟩ "value":"AAPL"}],"properties":{"country":{"description":"OPTIONAL ISO 3166-1 alpha-2 of the business register you mean (\"NO\", \"FI\", \"GB\", \"JP\", \"FR\", \"EE\", \"BR\"). Only affects a NAME lookup, and is often what separates the company you mean from a US namesake. When a name resolves to a register entity with no CIK, the SEC/CIK-keyed sections are reported under `sources_skipped` with reason `not_queried` — they were never asked, which is not the same as having failed.","type":"string"},"type":{"description":"\"company\" or \"ticker\ ⟨37 unchanged words⟩  or company name (e.g., \"Moderna\"). —A namesNAME resolvenow viaresolves through the national business registers as well as SEC EDGAR, company-nameso match.a non-US company returns its register identity and record rather than `resolved: false`.","type":"string"}},"required": ⟨4 unchanged words⟩ 

 ⟨170 unchanged words⟩ is mechanically not_established with NO model call made. For a boolean/derived field (e.g. "does this company sell to healthcare"), the quote only has to SUPPORT the value — a descriptive sentence about customers/products counts, the source need not state the answer verbatim. leadership_page_status ("fetched"|"not_found"|"not_attempted", plus leadership_note) says plainly whether a leadership/team page was actually read, so a named-person field (head_of_sales) coming back not_established is distinguishable from "this company just doesn't publish one" vs. "we never checked". model_output_empty:true means the model returned nothing usable (a transport/budget problem) — every field is not_established for THAT reason, never read as 20 individual "no" judgments. Use with a fixed question + schema across  ⟨36 unchanged words⟩ 

 ⟨3 unchanged words⟩ "value":"AAPL"}],"properties":{"country":{"description":"OPTIONAL ISO 3166-1 alpha-2 of the country whose business register you mean (\"NO\", \"FI\", \"JP\", \"GB\", \"FR\", \"EE\", \"BR\"). Narrows the national-register fan-out and is often the difference between the right company and a US namesake — \"Apple\" with country \"NO\" is a Norwegian company, not Apple Inc. Omitting it searches every register we can name, which is the right default when you do not know. company only; ignored for drug.","type":"string"},"type":{"description":"Entity type: \" ⟨87 unchanged words⟩ 

 ⟨126 unchanged words⟩ :{tool, args?, fields[], schedule}), "new_entity" (new business registrations from a state business-entity registry — params:{state:"CO", name_query?, entity_type?}), "tech_change" (a watched domain's website technology stack adds or drops a technology — params:{domains:["acme.com"], technologies?}). Delivery channels: feed (always on —  ⟨29 unchanged words⟩ 

 ⟨286 unchanged words⟩  schedule \"hourly\" needs the paid tier. new_entity: {state:\"CO\", name_query?:\"dental\", entity_type?:\"limited liability\"} — state is required and must be one of FL, NY, CO, OR, CT, TX, PA. tech_change: {domains:[\"acme.com\",\"example.org\"], technologies?:[\"Shopify\",\"Segment\"]} — domains required (1-200), technologies optional (exact names, case-insensitive) to narrow which detected technologies alert. Unknown keys in form_d/news_keyword/job_post/tool_diffform_d/news_keyword/job_post/tool_diff/new_entity/tech_change params are rejected at subscribe time.","type ⟨11 unchanged words⟩ ","form_d","news_keyword","job_post","tool_diff","new_entity","tech_change"],"type":"string"}},"required" ⟨4 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,475626 across 16851739 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 16851739 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,475626 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

 ⟨54 unchanged words⟩ FRED observations — params:{series_id:"UNRATE"}), "patent_grant" (new USPTO grants for an applicant), "clinical_trial" (new/updated ClinicalTrials.gov studies), "form_d" (new SEC Form D fundraise notices — params:{state?, industry?, min_amount?, exemption?}, all optional), "news_keyword" (GDELT keyword news alerts, metadata+link only — params:{query, lang?, domains?}), "job_post" (new public job-board postings — params:{ats?, board_token?} or {domain?}, plus optional title_query/location_query), "tool_diff" (re-runs any read-only tool on a schedule and fires on change — params:{tool, args?, fields[], schedule}). Delivery channels: feed (always on —  ⟨29 unchanged words⟩ 

 ⟨183 unchanged words⟩ \"PHASE3\"} (sponsor or condition required). form_d: {state?:\"CA\", industry?:\"Biotechnology\", min_amount?:500000, exemption?:\"06B\"} (all optional — omit all to watch every new Form D nationwide). news_keyword: {query:\"\\\"semiconductor sanctions\\\"\", lang?:\"eng\", domains?:[\"reuters.com\"]} (query required). job_post: EITHER {ats:\"greenhouse\", board_token:\"acme\"} (exact board) OR {domain:\"acme.com\"} (auto-detected), plus optional title_query/location_query substrings. tool_diff: {tool:\"form5500\", args?:{...}, fields:[\"headcount\"], schedule:\"daily\"} — re-runs that tool on schedule and fires when the named fields change; tool must be read-only and not need a Pipeworx-held platform key; schedule \"hourly\" needs the paid tier. Unknown keys in form_d/news_keyword/job_post/tool_diff params are rejected at subscribe time.","type":"object"},"type":{"description" ⟨4 unchanged words⟩ ","polymarket_edge","fred_series","patent_grant","clinical_trial","form_d","news_keyword","job_post","tool_diff"],"type":"string"}},"required" ⟨4 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,431475 across 16801685 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 16801685 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,431475 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

 ⟨462 unchanged words⟩ (zero releases across every requested category) returns errorthe SAME shape as a populated one — release_count:0, releases:[] — plus empty_reason:"no_releases_in_window" withand a widen-the-window`hint` hinttelling ratheryou thanto anwiden, emptyso arrayyou —never econbranch on the response shape and never have to guess whether zero means "nothing is scheduled" or "the lookup failed". Econ releases especially cluster on specific dates each month ⟨9 unchanged words⟩ 

 ⟨7 unchanged words⟩ :"string"},"type":"array"},"empty_reason":{"description":"Present ONLY on a zero-release window: \"no_releases_in_window\". The window was queried and nothing is scheduled — this is an answer, not a failure.","type":"string"},"hint":{"description":"Present ONLY on a zero-release window: what to change (usually a wider `hours`).","type":"string"},"notes":{"items":{"type":"string" ⟨117 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,350431 across 16591680 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 16591680 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,350431 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

 ⟨17 unchanged words⟩  the past year?"}],"properties":{"ask":{"description":"Alias for question.","type":"string"},"depth":{"description":"How many facets to ⟨43 unchanged words⟩ ,"thorough"],"type":"string"},"input":{"description":"Alias for question.","type":"string"},"message":{"description":"Alias for question.","type":"string"},"prompt":{"description":"Alias for question.","type":"string"},"q":{"description":"Alias for question.","type":"string"},"query":{"description":"Alias for question.","type":"string"},"question":{"description":"The research question, in natural language. Broad/multi-part is fine — decomposition is the point. Accepts query, q, prompt, text, input, ask, message as aliases.","type":"string"},"text":{"description":"Alias for question.","type":"string"}},"required": ⟨3 unchanged words⟩ 

{"examples":[{"key":"user_research_topic"}],"properties":{"k":{"description":"Alias for key.","type":"string"},"key":{"description":"Memory key to deletedelete. Accepts name, k, label as aliases.","type":"string"},"label":{"description":"Alias for key.","type":"string"},"name":{"description":"Alias for key.","type":"string"}},"required": ⟨3 unchanged words⟩ 

 ⟨2 unchanged words⟩ :"user_research_topic"},{}],"properties":{"k":{"description":"Alias for key.","type":"string"},"key":{"description":"Memory key to retrieve (omit to list all keys). Accepts name, k, label as aliases.","type":"string"},"label":{"description":"Alias for key.","type":"string"},"name":{"description":"Alias for key.","type":"string"}},"required": ⟨2 unchanged words⟩ 

 ⟨3 unchanged words⟩ "value":"AAPL"}],"properties":{"content":{"description":"Alias for value.","type":"string"},"data":{"description":"Alias for value.","type":"string"},"k":{"description":"Alias for key.","type":"string"},"key":{"description":"Memory key (e.g., \"subject_property\", \"target_ticker\", \"user_preference\"). Accepts name, k, label as aliases.","type":"string"},"label":{"description":"Alias for key.","type":"string"},"name":{"description":"Alias for key.","type":"string"},"text":{"description":"Alias for value.","type":"string"},"v":{"description":"Alias for value.","type":"string"},"value":{"description":"Value to store (any text — findings, addresses, preferences, notes). Accepts content, text, data, v as aliases; a non-string value is stored as JSON.","type":"string"}},"required": ⟨4 unchanged words⟩ 

 ⟨5 unchanged words⟩  fiscal 2023 revenue?"}],"properties":{"ask":{"description":"Alias for question.","type":"string"},"input":{"description":"Alias for question.","type":"string"},"message":{"description":"Alias for question.","type":"string"},"prompt":{"description":"Alias for question.", ⟨23 unchanged words⟩  Accepts query, q, prompt, text, input, ask, message as aliases.","type":"string"}," ⟨11 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,332350 across 16531659 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 16531659 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,332350 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,320332 across 16491653 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 16491653 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,320332 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

Beta version of ask_pipeworx: identical universal router (same 6,056320 tools, same arguments, same response shape)  ⟨68 unchanged words⟩ 

{"examples":[{"question":"What is the current US unemployment rate?"}],"properties":{"input":{"description":"Alias  ⟨55 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 6,056320 across 15721649 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

{"examples":[{"question":"What was Apple's fiscal 2023 revenue?"}],"properties":{"input":{"description":"Alias  ⟨53 unchanged words⟩ 

{"examples":[{"attribute":"revenue","company":"AAPL","period":{"fiscal_year":2023,"type":"annual"}}],"properties":{"as_of":{"description":"Past  ⟨363 unchanged words⟩ 

{"examples":[{"type":"company","values":["AAPL","MSFT"]}],"properties":{"type":{"description":"Entity  ⟨48 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 15721649 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ routes each to the right one of 6,056320 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

{"examples":[{"depth":"quick","question":"What is the current US unemployment rate and how has it changed over the past year?"}],"properties":{"depth":{"description":"How  ⟨71 unchanged words⟩ 

{"examples":[{"type":"company","value":"AAPL"}],"properties":{"type":{"description":"\" ⟨62 unchanged words⟩ 

{"examples":[{"url":"https://pipeworx.io"}],"properties":{"max_links":{"description":"Maximum  ⟨37 unchanged words⟩ 

{"examples":[{"message":"Fleet #2184 smoke test: verifying pipeworx_feedback example call returns non-empty.","type":"other"}],"properties":{"claim_token":{"description":"Read  ⟨144 unchanged words⟩ 

{"examples":[{"window":"7d"}],"properties":{"window":{"description":"24h  ⟨25 unchanged words⟩ 

{"examples":[{"topic":"Fed rate decision"}],"properties":{"event":{"description":"Single-event  ⟨77 unchanged words⟩ 

{"examples":[{"days":14,"window":"1wk"}],"properties":{"days":{"description":"Lookback  ⟨31 unchanged words⟩ 

{"examples":[{"limit":5,"window":"1wk"}],"properties":{"category_filter":{"description":"Comma-separated  ⟨369 unchanged words⟩ 

{"examples":[{"market":"will-the-fed-increase-interest-rates-by-25-bps-after-the-december-2026-meeting-20260729232808636","side":"buy_yes","size_usd":1000}],"properties":{"event":{"description":"Basket  ⟨95 unchanged words⟩ 

{"examples":[{"since":"30d","type":"company","value":"AAPL"}],"properties":{"since":{"description":"Window  ⟨62 unchanged words⟩ 

{"examples":[{"key":"target_ticker","value":"AAPL"}],"properties":{"key":{"description":"Memory  ⟨29 unchanged words⟩ 

{"examples":[{"type":"company","value":"AAPL"}],"properties":{"type":{"description":"Entity  ⟨89 unchanged words⟩ 

{"examples":[{"entities":["Pipeworx","Zapier"]}],"properties":{"_apiKey":{"description":"Optional  ⟨97 unchanged words⟩ 

{"examples":[{"package":"left-pad"}],"properties":{"package":{"description":"npm  ⟨35 unchanged words⟩ 

{"examples":[{"query":"supply-chain risk","text":"Apple Inc. reported fiscal 2023 revenue of $383.285 billion, driven by strong iPhone and Services growth. Net income was $96.995 billion. The company faced supply-chain risk in China during the quarter."}],"properties":{"limit":{"description":"Max  ⟨55 unchanged words⟩ 

{"examples":[{"topic":"finance"}],"properties":{"topic":{"description":"Optional  ⟨28 unchanged words⟩ 

{"examples":[{"claim":"Apple's fiscal 2023 revenue was $383 billion"}],"properties":{"claim":{"description":"Natural-language  ⟨67 unchanged words⟩ 

 ⟨8 unchanged words⟩ as ask_pipeworx — picks the right tool from 56,961056 across 15521572 sources, fills arguments, fetches the data — ⟨85 unchanged words⟩ 

 ⟨30 unchanged words⟩ on every tier. Grounded multi-source research across Pipeworx's 15521572 STRUCTURED data sources (SEC filings, FRED/BLS economics ⟨23 unchanged words⟩ , routes each to the right one of 56,961056 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩ 

 ⟨213 unchanged words⟩  real "no data", not a bug. `sources_skipped` is the third state: a leg we deliberately did NOT run, each entry carrying a `reason` token and a plain-English `detail` (the Purple Book is skipped for a filer SEC classifies outside the life-science SIC bands, since it lists only 351(a)/(k) biologics licence holders). Pass a ticker ("AAPL"), zero-padded CIK ⟨46 unchanged words⟩ 

 ⟨191 unchanged words⟩  partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. FILL CHECK: when the partition signal fires,  ⟨38 unchanged words⟩ 

 ⟨181 unchanged words⟩ daily closes of edge_pp_net (net of default slippage AND Polymarket's own taker fee — see polymarket_edges), not intraday.

 ⟨129 unchanged words⟩  85%/5%/50:1). EVERY OPPORTUNITY carries edge_pp_net (afternet of slippage AND Polymarket's own taker fee — fees_pp_applied itemises the fee component; see fees.ts for the published per-category schedule), kelly_fraction + kelly_fraction_half (capped at 0.25) ⟨111 unchanged words⟩ 

 ⟨89 unchanged words⟩ default 0.5). Edge is evaluated NET of slippage.slippage and Polymarket's own taker fee.","type":"number"},"min_kelly":{ ⟨159 unchanged words⟩  in percentage points per leg (default 0.3)., for bid/ask + thin depth cost that a last-trade price does not show. Subtracted from raw |edge| before ranking and Kelly sizing.sizing, PolymarketON hasTOP OF Polymarket's own taker fee — which is NOT zero trading(rate fees0.04-0.07 asdepending ofon 2024category, butread bid/askoff +each thinmarket's depthown typicallypublished eatsfee 20-50bpschedule; persee trade.fees_pp_applied on every row and fees.ts for the full schedule). Bump slippage for very thin partitions; drop to 0 if you have a smarter fill model.model — the fee still applies regardless.","type":"number"},"window":{ ⟨17 unchanged words⟩ 

 ⟨165 unchanged words⟩  dominant loss mode in real arb-bot P&L). FEES ARE NOT MODELLED HERE: vwap_fill_price/profit_usd are GROSS of Polymarket's own taker fee (rate 0.04-0.07 by category — see polymarket_edges/fees.ts), on top of which this tool prices depth-crossing cost; a thin-margin fill that looks clean here can still be net-negative after the fee.

 ⟨221 unchanged words⟩ query ran and why that event won). Fleet #2064: when two Polymarket candidates tie on resolution time `polymarket_selected_by` now SAYS so, names every tied slug, names the tie-break that actually decided it (the candidate whose metric_type matches the Kalshi series, else lexicographic slug order), and states whether the winner's metric matches the Kalshi series — it used to assert "picked the soonest-resolving" byte-identically on calls that returned DIFFERENT events, because the tie was settled by upstream fetch arrival order. RESPONSE: each venue's leg-by-leg prices (raw probability  ⟨52 unchanged words⟩  probably not the same question), temporal_mismatch (theythe resolvetwo inevents are about different SUBJECT months — e.g. Kalshi "CPI in October" vs Polymarket "September Inflation"), temporal_alignment_unknown (the resolutionsubject month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike dateevent yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified  ⟨67 unchanged words⟩ ,aligned} tells you whether the two events resolveare inabout the same SUBJECT calendar period, in EITHER mode;mode — this is the period the question is ABOUT (e.g. "September" for a CPI release that settles in October), not necessarily when either side settles; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_noteFleet is#2062: this used to compare Polymarket's settlement date against Kalshi's subject month and call a standingmatch disclosure— fixed to compare subject month to subject month on both sides. FEES: Kalshievery chargestop_spreads_pp per-contractand tradinglow_confidence_pairs[] feesrow carries edge_pp_gross (== |spread_pp|), Polymarketfees_pp, doesedge_pp_net, notnet_positive, and thisBOTH toolvenues' doestaker notfees modelitemised Kalshi'sas kalshi_fee_pp and polymarket_fee_pp (plus polymarket_fee_rate, polymarket_fee_category, polymarket_fee_basis). Kalshi leg: fee schedule= —ceil(0.07 every* spread_ppcontracts is* grossP * (1-P) * 100) / 100 dollars per order, notverified aagainst netkalshi.com/docs tradeableand edge.corroborating spread.resolution_source_noteexplainers isas theof second2026-09-12. standingPolymarket disclosureleg: thefee two= venues'shares RESOLUTION× SOURCESrate are× neverp compared,× so(1-p) awith Polymarketrate marketby settlingcategory on(crypto a0.07, Binancesports/economics/culture/weather/other 1-minute0.05, candlefinance/politics/mentions/tech 0.04, geopolitics and aworld Kalshievents eventfee-free), strikingverified onagainst Kalshi'sPolymarket's own indexdocs as of 2026-09-13 and read off each market's published fee parameters rather than inferred. Both amortized at a different100-contract hourreference willsize. Before fleet #1927 the Polymarket leg carried modeled gas only, which made every edge_pp_net here optimistic by up to ~1.75pp; spreads that no longer clear are the correction. Spread-crossing cost is still beNOT shownmodeled sideon the Polymarket leg (no live order book is fetched by this tool). spread.fees_note carries the same disclosure. RESOLUTION EQUIVALENCE (fleet #1909): every top_spreads_pp and low_confidence_pairs[] row now also carries resolution_equivalent ("true"|"false"|"unclear") and, when not "true", resolution_warning naming what differs — computed ONCE per event pair (not per leg) via resolution_audit/resolution_diff off one representative leg from each side, since the settlement mechanism is normally shared across every leg in one event. A non-equivalent or unclear pair is NEVER suppressed, only labelled — partread ofresolution_warning anybefore spread_pptreating mayspread_pp beas a differencereal incross-venue contractdisagreement rather than a difference in opinion.contract. spread.resolution_audit carries the full underlying audit (source/timestamp/timezone/precision/evidence_standard/void_handling for both sides) and spread.resolution_source_note is the standing disclosure explaining the methodology and its "unclear" caveat. Call resolution_audit/resolution_diff directly for a specific pair of legs if you need a non-representative-sample breakdown. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair ⟨40 unchanged words⟩ 

 ⟨9 unchanged words⟩ ask_pipeworx — picks the right tool from 5,957961 across 1552 sources, fills arguments, fetches the ⟨87 unchanged words⟩ 

 ⟨69 unchanged words⟩ routes each to the right one of 5,957961 tools IN PARALLEL, and returns a findings  ⟨216 unchanged words⟩