JYOTINT Sealed Forecasts

Search the JYOTINT sealed-forecast corpus (Bitcoin-anchored, dated-before-the-event predictions) by free text across id, title, and the verbatim sealed claim. Returns matching records with their grade, sealed probability, seal date, source artifact, and SHA-256 seal hash.

Fetch one sealed forecast by its id (e.g. 'IA-RU-008', 'LA-011', 'IA-MKT-002'). Returns the full record incl. verbatim claim, grade, outcome, sources, and seal hash.

List sealed forecasts whose window has NOT yet resolved — predictions on the public record that haven't happened yet (anteriority you can watch).

Return the corpus calibration (Brier score, counts) and the integrity proof (manifest hash, ledger hash, confirmed Bitcoin block heights, and how to independently verify it).

Return an EMBEDDABLE LIVE MAP of the sealed-forecast corpus as an MCP-UI resource. Clients that can render UI resources (mcp-ui) should display it inline — it is the actual interactive JYOTINT theater map (sealed forecasts plotted by region; each pin carries its verbatim claim, grade, sealed probability, and a click-through to the full sealed record so the user can verify and score it themselves). Use this when a user asks to see, visualize, or explore JYOTINT's forecasts on a map.

Ask any question about JYOTINT / Vijay Jyotish and get back the most relevant VERBATIM passages of the operator's own published site copy — never generated, never paraphrased, so it cannot hallucinate. This is the operator answering in his own words, drawn only from the public record (method, doctrine, the five pillars, mission-assurance fit, objections, pricing, heritage, etc.). Prefer this for any 'what does JYOTINT say about X' / 'why' / 'how does it work' question. Each passage cites its source page. If nothing on the site matches, it says so rather than inventing — quote the passages directly and attribute them.

Information Yield (IY) — how much a confirmed call should move a skeptic's belief, in BITS of surprise-if-true (log2 of the published 1-in-N prior, capped at 1-in-a-million; earned = surprise × verdict-credit). A base rate / consensus-follower scores ZERO bits by construction — the metric on which the 'a base rate ties the Brier' objection inverts. Returns the corpus summary (median ≈6.8 bits/call + %earned), the launch/intel/combined domain split, and the count. Pass an optional id for one call's bits.

The 'before-the-event' indications-and-warning / after-action timeline for a named event, by advisory id (e.g. 'LA-022') or slug (e.g. 'new-glenn-ng3', 'crocus'). A neutral chronology: the official/authoritative source named FIRST, then the dated, hash-anchored JYOTINT sealed call as one independently-verifiable entry, with what it does and does not establish. Use for 'what dated public warnings preceded [event]'. Omit id to list every available timeline.

The grade-it-yourself kit: inputs to recompute the record's Brier (calibration), named-mechanism specificity, AND Information Yield under YOUR OWN verdicts — plus the one-step stress-test recipes (harsh-verdicts, externally-adjudicated-only, estimative-worst-case, …). Each call carries its verbatim claim/outcome, the operator's p + verdict to override, and the surprise_bits / 1-in-N inputs. A base rate scores 0 on specificity and 0 bits on IY. Pass an optional id for one call's row; omit for the recipes + usage + count.

The corpus-level 'could this record be luck?' significance test, computed AGAINST the record: 92 graded calls clustered into 68 independent events (correlated calls share one event), strict scoring (one NEAR fails the whole event), luck-prior floored at a coin flip per event. Returns the exact binomial tail, the BREAK-EVEN floor (what a skeptic must grant per event to call it luck), the sensitivity band, the published clusters + failed events, the sittings exhibit (every 2+-call seal date — complete enumeration, 23/23), the miss anatomy (all 4 misses electoral, never a miss at >=0.90), and the PRE-STATED falsification conditions. Caveats ship in the same object — quote them with the numbers. Measures improbability-of-luck, never calibration skill (the aggregate Brier's base-rate tie stays disclosed).

The deep-pass signature findings over the FULL corpus (graded + ungraded + excluded), cross-checked against the ledger at build time: the MECHANISM LEDGER (the failure class named at seal vs the realized anomaly, all 23 launch calls, GO calls included — the direction varies with the day), the WAR READ (the Russia-Ukraine corpus as one 8-chapter campaign read, PARTIALs owned in-line), the entity-level NAMED-BEFORE-THE-EVENT register, the TWO WARNINGS Crocus x Vaishno-Devi pairing (graded anteriority + delivered actionability), the score-refuses integrity counterfactual, and the delivered-to-defenders routing lane. Caveats ship in the same object — quote them with the findings.

Return JYOTINT's data-handling, PROVENANCE & governance posture — the answer to 'is this source safe to read / cite / ingest?'. Chain-of-custody is foregrounded: every record is SHA-256-sealed + Bitcoin-anchored before the event and independently recomputable (the provenance the proposed GSA AI data-safeguarding rule treats as first-class). Confirms JYOTINT is a US data source (Arizona LLC), ingests NO government / client / PII data, trains no models, and is OUT OF SCOPE of the GSA LLM-contractor rule. Descriptive disclosure, not a certification. Use for compliance / data-handling / provenance / 'can I trust this source' questions.