Jawz

Growth pillar indicators, the detail behind the Business cycle card of get_dashboard (its Growth, Jobs and Investment rows) and the regime's Mood row: industrial production (IPMAN, the ISM proxy), consumer sentiment (U Michigan), the 2s10s yield curve, initial claims, plus the Atlanta Fed GDPNow nowcast of the quarter in progress. growth_vote_inputs holds the three inputs of the business cycle's growth vote, each with its word and dated observation: output (IPMAN three-month change), jobs (initial claims four-week average against twelve weeks earlier) and investment (BEA real private fixed investment in information-processing equipment and software, A679RX1Q020SBEA, year on year, with its quarter), plus the vote's rule; the vote itself is applied in get_macro_regime. GDPNow carries its own reference_quarter, the publication date of the estimate, and the previous estimate of the SAME quarter, so its direction of travel is readable; it is reported, not scored, so it does not move the classification. When no estimate is on file the block reports status: unavailable and says so in staleness_flags — not published, which is not the same as zero. Returns classification (green/yellow/red), the growth pillar's own score, separate from the vote; read_complete is false when a series failed to read.

get_growth_indicators

Any card of the Jawz Dashboard (get_dashboard), or one of its rows, over time, each at its own print dates: the weekly reads for the weekly cards, the release dates of the series behind a row for the rest. With no arguments it returns the catalogue: every card and indicator key with its kind, cadence, unit, source and the earliest date it reaches. card alone returns that card's badge (indicator defaults to 'badge'); card plus indicator returns that row. from and to (YYYY-MM-DD) set the window: to defaults to today and from to one year before to; the history reaches back 365 days (store of value starts 84 days later), and a clamped window is echoed as requested_from and effective_from. Every point carries Jawz's word for that date and point_in_time. What Jawz computes (the six badges, the four-bank money total, the dollar effect, US money, the growth vote) also carries the value and its display at every point. Published series that Jawz passes through unchanged (mood, jobs, BEA investment, prices, rates, credit, the dollar, gold, bitcoin, data centres, chips, builders' capex, power) carry Jawz's word per print plus the source (provider, series, link and, for FRED series, the ALFRED vintage link), because the full numbers stay with the publisher. The answer adds the rule in one sentence, transitions (every change of word), runs, and the current word with the date it has held since (for a badge, the card's own held_since). History applies today's rules to what was published by each date (rules: 'today'): method_events lists rule changes in the window that moved the card, and published_differs lists, for the regime and business-cycle badges, the dates where what Jawz published that day differs. The four-bank money rows add the coverage basis, a constant three-bank total and coverage and PBoC-statement events. An unknown card or indicator, a malformed or future date, or a date before the window returns an error naming the valid keys or range. A cold window that runs out of compute time returns the points ready with partial: true and pending_from; the same call again continues from the points already kept. Read-only, no account needed. Information, not investment advice.

get_indicator_history

Inflation pillar indicators, the detail behind the Prices row of the Business cycle card of get_dashboard: headline + core CPI, headline + core PCE (YoY and MoM), 5Y/10Y breakevens, wage growth. Returns classification (supportive/neutral/headwind).

get_inflation_indicators

Global-liquidity read-history — a timeseries of central-bank liquidity over recent weeks. Returns one row per sample date with the full decomposition (Fed / ECB / BoJ / PBoC in USD trillions), the active basis (g4/g3/us_fallback), the supportive/neutral/draining classification of that week's read, and US net liquidity (us_net_t: Fed balance sheet minus the Treasury General Account minus reverse repo, USD trillions) with its own classification (us_net_class), plus coverage (basis) changes, China-leg publication steps, and classification changes as events. The held money condition, which changes only after two consecutive weekly reads agree, is in get_macro_regime and the Money card of get_dashboard. History companion to get_financial_conditions (Chapter 1 Mode 1.5 Global Liquidity Read). Reading note, enforced by the artifact: when the basis flips g4↔g3 (China PBoC publication freshness), the headline total moves by the ~$7T China component, which is a coverage change rather than a liquidity move. The window trend is therefore computed on constant G3 basis, and every basis flip is listed with an explicit note. A China-leg publication step is a DIFFERENT event and is reported separately: PBoC publishes monthly ~15 days in arrears, so on the day a new statement is recorded the PBoC leg absorbs a whole month of balance-sheet change (plus FX) in one step — real change, but not change that happened on that date, and not the same thing as a coverage flip. The response includes a 'presentation' object whose 'display_markdown' is a pre-formatted table; 'data.rows' and 'summary' carry the same values structured. Rows are provenance-tagged 'observed' (live that day, true vintage) or 'reconstructed' (point-in-time from vintage data — each series as it was published on that date, ~4 months deep). Defaults to the last 12 weeks, weekly. get_indicator_history covers any card or row of get_dashboard over a year, at its own print dates.

get_liquidity_history

Get metadata and chapter manifest for a loop by slug. Returns loop info and the list of chapter nodes with titles — no chapter content. All active loops are navigable by anyone.

get_loop

The current macro regime (GREEN / YELLOW / RED) and business cycle (SPRING / SUMMER / FALL / WINTER) with the evidence behind them: the detail behind the Regime and Business cycle cards of get_dashboard. The regime combines consumer mood (U Michigan sentiment) with money (the global-liquidity condition), and the money condition changes only after two consecutive weekly reads agree: data.details.liquidity_condition shows this week's raw read, the held class, how many agreeing reads are still needed, and the margin to the line. The business cycle crosses growth with prices. Growth is a vote of factory output (IPMAN trend), jobs (initial claims) and investment (BEA real investment in information-processing equipment and software), two of three deciding, and the season changes only when two prints in a row agree: data.cycle carries the vote, the dated prints and held_since. The response opens with the Jawz Dashboard card: the six-reading card as markdown at the top of presentation.display_markdown (above a horizontal rule), the same object at data.read, and the card as a PNG image content block after the text. Below the card, display_markdown carries the regime write-up and its tables (regime inputs, the growth vote, the growth and inflation composites, asset-class tilts); 'tables' is their structured form and 'data' holds the raw values. A 'provenance' block lists each input with its as-of date and age in days. get_indicator_history gives the regime, the cycle or any of their rows over time.

get_macro_regime

Live prices for one or more holdings, and the answer shows its work. Resolves raw tickers (stocks, ETFs, crypto, international listings) and returns price, value, and day change per symbol, plus per holding: what it resolved to (asset: type, exchange, ISIN, provider id; asset.isin is filled when you pass an isin hint or the provider profile carries one, and is null otherwise — it is not looked up), how surely (resolution: matched_by isin|qualified_symbol|bare_symbol, candidates, mismatch against the caller's hints), the native quote with its own time (quote), the FX rate actually applied, dated and sourced (fx), and the position value native and in the base currency. Optional per-holding hints — isin (equities/ETFs/funds), exchange, asset_class — narrow resolution; a hint that contradicts the result is reported, not silently overridden. A bare ticker is resolved listing first: when the same symbol is both a US listing and a crypto token that is not a known major coin (HOOD, MSTR, and tokenized-stock proxies such as ALAB, LITE, NBIS), it prices the listing, never the token; the token is priced only when no such listing exists. A known major coin that shares its symbol with a well-known US listing (STX is Stacks and Seagate) stays the coin, with a line warning that names the listing and how to get it (qualify it, or asset_class 'equity'). A bare ticker shared by differently named funds on other venues (DRAM) is priced with a line warning naming the alternatives and their qualified symbols, counted in resolution.candidates. Qualifying as NASDAQ:X / X.US picks the US listing explicitly. Line warnings are in each holding's warning; a summary is in the top-level warnings. base_currency defaults to USD; 'native' returns unconverted quotes.

get_prices

Macro regime read-history — a timeseries of how the regime and its drivers have moved over recent weeks. Returns one row per sample date (regime color, business-cycle quadrant, growth + inflation class, consumer sentiment, global liquidity, dominant risk, confidence) plus the transitions between them (e.g. SUMMER → FALL). Provides the observed history behind a 'what changed since …' question, rather than a comparison of two separate point reads. Rule changes that moved the published colour or season without the market moving are listed in data.events as method events (kind 'method'), each dated the first day the new rule was live, with what changed and why: for example the money condition waiting for two consecutive weekly reads (2026-09-25) and the growth vote with two prints to change the season (2026-09-30). Observed rows keep what Jawz published that day under the rules then in force. Reading note, enforced by the artifact: the Liquidity column steps for two reasons that are NOT the market, and both are listed as first-class events in summary.liquidity_events — a g4↔g3 coverage flip (the whole PBoC component entering or leaving the sum: not a liquidity move at all), and a China-leg publication step (PBoC publishes monthly ~15d in arrears, so the day a new statement is recorded the column absorbs a whole month of change: real change, wrong date). get_liquidity_history carries a constant-basis G3 series that is immune to both. The response includes a 'presentation' object whose 'display_markdown' is a pre-formatted table; 'data.rows' and 'summary' carry the same values structured. Each row is provenance-tagged: 'observed' (captured live that day — true vintage) or 'reconstructed' (computed point-in-time from vintage data — each series as it was published on that date, so later revisions are excluded; depth-limited). Defaults to the last 12 weeks, weekly. get_indicator_history covers any card or row of get_dashboard over a year, at its own print dates.

get_regime_history

Orientation for a new Jawz connection, and for questions about what Jawz is, what it covers, or how it is used. Returns where to start (start_here: get_dashboard, the Jawz Dashboard, which gives the state of the world in six readings), a description of the Jawz Loop, example opening prompts, a one-line live market read drawn from the current data layer, a note on the plain-English glossary included in Jawz responses, and a link to the full guide.

get_started

Past week's data releases with H.4.1 net liquidity update. Anchored to Friday — most current when run Friday morning or later. Each release classifies actual vs consensus where BOTH are on file (both Mako-curated): `surprise` is hot / modestly hot / in-line / modestly cool / cool on the headline metric, `vs_consensus` is the same comparison stated neutrally as above/below/in-line, and `metrics` breaks it down per metric. hot/cool is DIRECTIONAL versus consensus, not a verdict — a hot CPI and a hot payrolls print mean opposite things for the same book. `surprise: "n/a"` means the comparison could not be made; `implication` names which half is missing. consensus_provenance.age_days is measured at week_ending, not at call time, so re-asking for an earlier week returns the same age it did the first time.

get_weekly_data_releases

List all available Jawz loops. Returns loop metadata, access status, and which loop is currently active for this user. Every published loop is free and open. Deprecated loops you are entitled to are included with deprecated: true.

list_loops

Returns a chapter's published framework text: its modes, the questions each asks, and the output format it describes. The framework is reference material for the assistant to apply as it judges appropriate. Repeat calls return the same chapter content — the text is not regenerated per call. Each call appends one usage-counter row and returns a new invocation_id used for feedback.

run_chapter

Returns the published framework text for one named mode within a chapter, rather than the full chapter. Repeat calls return the same mode content — the text is not regenerated per call. Each call appends one usage-counter row and returns a new invocation_id used for feedback.

run_mode

Score how a single position's regime fit has drifted since entry. Returns regime_at_entry, regime_now, fit_score_at_entry, fit_score_now, drift_score (now - entry), drift_label (improved/stable/deteriorated/review_now), explanation, and review_questions. No buy/sell recommendation — output is observational. Supports Chapter 4 Mode 4.2 (Position Retrospective) for single-name regime-fit review and Mode 4.3 (Thesis Status Sweep) for per-position drift across the book.

score_position_drift