ai.jawz/jawz

Fetch the full content of a chapter by loop slug and node. Loops not marked open require entitlement; every published loop is currently open and free. Does not log an invocation; run_chapter is the variant that runs the framework and logs.

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.

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.

Freshness status for every data source Jawz reads: per-source release date, latest observation date, expected cadence, age in days, and whether any source is stale or unavailable. Also reports whether the ingestion pipeline is keeping up, and carries plain-language notices when a scheduled update has not arrived. Applies when the reliability of a figure depends on how current its underlying data is.

Portfolio-wide drift scan. Iterates Decision Records, calls score_position_drift on each, returns flagged positions with severity + why_flagged + review_questions. Flag types: drift_severe (review_now), drift_meaningful (deteriorated), fit_low_structural (score ≤2 but unchanged since entry — low by design, not decay), fit_low_decayed (score ≤2 AND below entry fit — deteriorated after entry), conviction_gap (|gap| ≥3), thesis_undocumented (entry_date or thesis missing). Backs Chapter 4 Mode 4.3 (Thesis Status Sweep) as the portfolio-wide drift scan; flagged names feed a Mode 4.2 (Position Retrospective).

ETF look-through for Chapter 2 Mode 2.2 (Concentration Check). Given ETF ticker(s), returns each fund's top holdings with weights so the AI can overlay them with the user's direct positions and surface hidden single-name concentration. Each profile carries source='live' (Vanguard API, fresh) or source='catalog' (dated snapshot — see as_of). Holdings are TOP-N only, so any true-exposure figure computed from this is a floor, not exact. Bond and commodity ETFs return no holdings by design. Tickers not in the catalog come back in unknown_tickers; their contents are not known to Jawz and no holdings are returned for them.

Scheduled US macro events (FOMC + CPI + NFP + PCE) with dates and consensus. Consensus values are Mako-curated and arrive with provenance (source, source_url, published_at, age_days). An event with no curated consensus carries consensus: null, which means the value is not published rather than zero. Mode 1.2 covers the qualitative-scenario path for events whose consensus is not published. consensus_metrics_expected lists the metric keys a complete consensus would carry for that event type. Market-implied pricing (what_is_priced / CME FedWatch) is a separate quantity and remains deferred. COVERAGE: only fomc, cpi, nfp and pce have dates in this calendar. ecb, boj and boe are accepted for consistency with the consensus vocabulary but carry NO dates, so filtering to them returns an empty list and says so in staleness_flags — that is 'not tracked here', never 'none is scheduled'. Coverage also runs to a fixed last date; a window past it is flagged rather than silently short.

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.

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).

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

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.

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 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.

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), 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. Symbols that collide with tokenized-stock proxies on the crypto side (ALAB, LITE, NBIS, GLW, CBRS, DRAM, AIPO) resolve to the listed instrument, never the token; qualifying as NASDAQ:X / X.US does the same explicitly. base_currency defaults to USD; 'native' returns unconverted quotes.

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.

Orientation for a new Jawz connection, and for questions about what Jawz is, what it covers, or how it is used. Returns 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.

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.

Read the Jawz World Brief — the weekly Mako-bylined market read published at jawz.ai/brief. Returns the latest edition by default, or a specific one by slug (YYYY-MM-DD). Every claim in a brief traces to a Jawz tool read from its week. Setting list_only:true returns the available editions without their content.

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.

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.

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.

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.