jawz

Quality 63 / 100needs work

24 tools, about 8,549 tokens to load them all · tool set 48f6c6c1f9e0 · tools last changed 2026-10-19 · checked 2026-10-19 10:52 UTC

Tool changes

• 2026-10-19get_data_healthchangedoutput schema
• 2026-10-14get_china_liquiditychangeddescription
  before

  Read the latest Mako-curated PBoC balance-sheet publication (CNY trillions + source URL + as_of_month + note). Public read — suitable for surfacing directly when explaining the China leg of global liquidity. The same value is also embedded in get_financial_conditions.pillars.global_liquidity.components.china; this tool exists for direct/auditable access.

  after · 92% of words in common

  Read the latest Mako-curated PBoC balance-sheet publication (CNY trillions + source URL + as_of_month + note). Public read — suitable for surfacing directly when explaining the China leg of global liquidity. The same value is also embedded in get_financial_conditions.pillars.global_liquidity.components.china and is the PBoC leg of the Money card of get_dashboard; this tool exists for direct/auditable access.

• 2026-10-14get_inflation_indicatorschangeddescription, output schema
  before

  Inflation pillar indicators: headline + core CPI, headline + core PCE (YoY and MoM), 5Y/10Y breakevens, wage growth. Returns classification (supportive/neutral/headwind).

  after · 65% of words in common

  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).

• 2026-10-14get_growth_indicatorschangeddescription, output schema
  before

  Growth pillar indicators: industrial production (ISM proxy), consumer sentiment, yield curve, initial claims, plus the Atlanta Fed GDPNow nowcast of the quarter in progress. 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).

  after · 51% of words in common

  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.

• 2026-10-14get_financial_conditionschangeddescription
  before

  Full financial conditions read: global liquidity (Fed + ECB + BoJ central-bank balance sheets, FX-converted to USD; PBoC included when a fresh Mako-curated publication is available — basis 'g4' vs 'g3'), real yields, HY/IG credit spreads, DXY, VIX. US net liquidity is retained as a sub-component. Returns composite + direction + per-pillar classifications + drivers. The `scope` and `scope_note` fields tell you whether the read is G4 or G3, and the China sub-component carries Mako-curated provenance (as_of_month, source_url, note). Pass summary_only:true for the lightweight one-line read used in regime composition.

  after · 59% of words in common

  Full financial conditions read, the detail behind the Money and Financial conditions cards of get_dashboard (and the regime's Money row): global liquidity (Fed + ECB + BoJ central-bank balance sheets, FX-converted to USD; PBoC included when a fresh Mako-curated publication is available — basis 'g4' vs 'g3'), the 10-year real yield with its nominal and breakeven legs, HY/IG credit spreads, the dollar index (DXY), VIX. Inside global liquidity: us_net_liquidity (Fed balance sheet minus the Treasury General Account minus overnight reverse repo, with 4- and 12-week changes, its own classification and dated inputs; a supporting read, not part of the regime light) and change_decomposition (for the 4- and 12-week windows, how much of the change in dollars came from the balance sheets themselves and how much from exchange rates, which dominated, and the method). Returns composite + direction + per-pillar classifications + drivers. The `scope` and `scope_note` fields tell you whether the read is G4 or G3, and the China sub-component carries Mako-curated provenance (as_of_month, source_url, note). Pass summary_only:true for the lightweight one-line read used in regime composition.

• 2026-10-14get_indicator_historyadded

  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.

• 2026-10-14get_conditions_historychangeddescription
  before

  Financial-conditions read-history — a timeseries of how conditions have moved over recent weeks. Returns one row per sample date with the composite (loose/neutral/tight), direction (easing/stable/tightening), and every pillar's value + class: 10Y real yield, HY/IG credit spreads, DXY, VIX, global-liquidity class. The rate legs behind the real yield are exposed numerically too (dgs10_pct, t10yie_pct, t5yie_pct, t10y2y_pct), so a real-yield move can be read as nominal-led or breakeven-led rather than only as a fused number. Completes the Chapter 1 history trio with get_regime_history (the judgment) and get_liquidity_history (the flow) — this is the price of risk. Surfaces trajectory that a point read hides (e.g. HY spreads widening for six straight weeks while VIX stays calm), and grounds 'conditions are tightening' statements in observed pillar changes. Window deltas per pillar are in 'summary.deltas'; composite/direction/pillar classification changes are listed as events. 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.

  after · 93% of words in common

  Financial-conditions read-history — a timeseries of how conditions have moved over recent weeks. Returns one row per sample date with the composite (loose/neutral/tight), direction (easing/stable/tightening), and every pillar's value + class: 10Y real yield, HY/IG credit spreads, DXY, VIX, global-liquidity class. The rate legs behind the real yield are exposed numerically too (dgs10_pct, t10yie_pct, t5yie_pct, t10y2y_pct), so a real-yield move can be read as nominal-led or breakeven-led rather than only as a fused number. Completes the Chapter 1 history trio with get_regime_history (the judgment) and get_liquidity_history (the flow) — this is the price of risk. Surfaces trajectory that a point read hides (e.g. HY spreads widening for six straight weeks while VIX stays calm), and grounds 'conditions are tightening' statements in observed pillar changes. Window deltas per pillar are in 'summary.deltas'; composite/direction/pillar classification changes are listed as events. 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.

• 2026-10-14get_liquidity_historychangeddescription
  before

  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), and the supportive/neutral/draining classification, plus coverage (basis) changes, China-leg publication steps, and classification changes as events. 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.

  after · 83% of words in common

  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.

• 2026-10-14get_regime_historychangeddescription
  before

  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. 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). Do not read that column as a trend without checking them; 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.

  after · 80% of words in common

  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.

• 2026-10-14get_macro_regimechangeddescriptionmeaning changed
  before

  Get current macro regime (GREEN/YELLOW/RED) with business cycle positioning. The response carries the same values three ways: 'presentation.display_markdown' is a pre-formatted rendering with tables, 'tables' is the structured form of those tables, and 'data' holds the raw values. A 'provenance' block lists each input with its as-of date and age in days.

  after · 27% of words in common

  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.

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