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296,600 tools. Last updated 2026-07-14 04:07

"Western Union" matching MCP tools:

  • Aggregate dossier check: Run all 10 Domain Dossier checks — dns, mx, spf, dmarc, dkim, tls, redirects, headers, cors, web-surface — in parallel and return all results in a single response. Use when you need a comprehensive domain health snapshot in one call; counts as ONE paywall call regardless of how many checks run. For a single focused check, prefer the individual dossier_* tools to minimise latency. Fires all 10 checks concurrently via Cloudflare DoH or direct HTTPS, 5 s per-check timeout. Returns a JSON object keyed by check id (dns, mx, etc.), each value a CheckResult discriminated union ({status:"ok",...} or {status:"error", reason}).
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  • Recommends crystals based on zodiac sign, chakra, or intention keyword. At least one filter is required. Returns crystals that match the most criteria first. SECTION: WHAT THIS TOOL COVERS Scoring: zodiac match scores 3, chakra match scores 2, keyword match scores 1. Crystals matching multiple filters rank highest. Returns up to limit results (default 5, max 20). Valid chakras: Root, Sacral, Solar Plexus, Heart, Throat, Third Eye, Crown. Valid zodiac signs: English Western zodiac names (Aries, Taurus, etc.). Intention keyword is matched against each crystal's keywords[] list (partial match). Not a Jyotish prescription — does not account for natal chart or planetary periods. For chart-based gem prescription use asterwise_get_gemstone_recommendations. SECTION: WORKFLOW BEFORE: None — standalone for consumer apps. AFTER: asterwise_get_crystal — get full detail on any recommended crystal. SECTION: INPUT CONTRACT At least one of: zodiac_sign, chakra, intention must be provided. zodiac_sign (optional): English zodiac sign, e.g. 'Taurus', 'Scorpio'. chakra (optional): One of Root, Sacral, Solar Plexus, Heart, Throat, Third Eye, Crown. intention (optional): Keyword string, e.g. 'protection', 'abundance', 'love'. limit (optional int, default 5, max 20): Maximum results to return. SECTION: OUTPUT CONTRACT data.total (int — number returned) data.filters_applied{} — the filters used data.crystals[] — matched crystals sorted by score descending SECTION: RESPONSE FORMAT response_format=json — recommendation object. response_format=markdown — formatted recommendations. Both return identical data. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (upstream): No filters provided → 422. Invalid chakra name → 422. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_crystal_by_planet — Vedic planet filter only. asterwise_get_gemstone_recommendations — natal chart house-lordship gem prescription with contraindications.
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  • Core dossier check: Verify DNSSEC chain-of-trust for a domain (DS, DNSKEY, AD flag). Use to confirm the zone is signed and resolvers accept the chain; prefer dossier_dns for raw record types or dossier_full for the complete audit. Fires Cloudflare DoH DS and DNSKEY queries with DO=1; 8s timeout. Returns a CheckResult discriminated union with { dnssecEnabled, adFlag, ds[], dnskey[] } on success.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Core dossier check: Look up a domain's MX (mail exchanger) records and return them sorted ascending by priority. Use when verifying inbound-mail routing or as a precursor to SPF or DMARC checks; prefer dns_lookup with type=MX if you only need the raw DNS answer without the ranked view. Queries Cloudflare DoH (1.1.1.1), follows CNAME aliases, 5 s timeout. Returns a CheckResult discriminated union: on success, {status:"ok", records:[{exchange, priority},...]} sorted by priority; on failure, {status:"error", reason}.
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  • Get the SCEvent stream for a session — all observed transitions reconstructed from status_history. Returns events[] with discriminated union by event_type (sc.scheduled, sc.confirmed, sc.completed, sc.delivered, sc.verified, sc.cancelled, etc.), plus stream_completeness ("complete" | "partial_pre_trigger") and pagination cursor. Events carry origin="reprojected_from_status_history" and canonical SCEvent shape per docs/protocol/sc-event-canonical-schema-2026-04-18.md §7.2. Filters: event_types (e.g. ["sc.delivered"]), from_sequence (cursor), limit (default 50, max 500). PII note: delivery_proof clinical fields (summary, outcome, next_steps) are returned only for admin-scoped keys. IMPORTANT: backfilled sc_resolved timestamps do NOT emit sc.resolved events in this stream (Forma B, see decisions log 2026-04-18-lifecycle-history-backfill-policy). For current resolution status, use lifecycle_get_state.sc_resolution. Requires X-Org-Api-Key.
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  • Calculate a complete Western natal chart using the tropical zodiac and Swiss Ephemeris. Returns 10 planet positions with Placidus (or chosen) house placements, essential dignities, all active aspects, and element/modality/hemisphere balance statistics. SECTION: WHAT THIS TOOL COVERS Tropical natal chart: Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, Pluto. Each planet returns tropical longitude, sign, house (1–12), retrograde flag, dignity label (domicile/exaltation/detriment/fall/peregrine), dignity score (domicile +5, exaltation +4, triplicity +3, term +2, face +1, detriment -5, fall -4), is_exaltation_degree (within 1° of exact exaltation), dignity_disputed (true for outer planets where exaltation/fall is disputed among modern astrologers). Aspect orbs: conjunction/opposition 5°, square/trine 5°, sextile 3°, minor aspects 1.5°. Not Vedic sidereal (asterwise_get_natal_chart). SECTION: WORKFLOW BEFORE: None — this tool is standalone. AFTER: asterwise_get_western_transits_daily — layer current transits over this natal chart. AFTER: asterwise_get_western_synastry — compare this chart against a partner's chart. AFTER: asterwise_get_western_solar_return — annual return chart for the current year. SECTION: INPUT CONTRACT birth.date — YYYY-MM-DD. Example: '1985-11-12' birth.time — HH:MM (24-hour local time). Example: '06:45' birth.lat — Decimal degrees, north positive. Example: 19.076 (Mumbai) birth.lon — Decimal degrees, east positive. Example: 72.8777 (Mumbai) birth.timezone — IANA timezone string. Example: 'Asia/Kolkata', 'America/New_York', 'Europe/Rome', 'UTC'. Default: UTC. IMPORTANT: Timezone defaults to UTC — always supply the correct local timezone for accurate house cusps. An incorrect timezone shifts the Ascendant. birth.house_system — 'placidus' (default, most common), 'koch', 'equal', 'whole_sign'. Placidus is standard for most Western traditions. Whole sign is traditional/Hellenistic. NOTE: house_system is accepted here but silently ignored by transit, return, synastry, composite, and progression endpoints — those always use the birth location coordinates without house-system selection. ayanamsa — always tropical regardless of any value supplied; field is not present. SECTION: OUTPUT CONTRACT data.zodiac (string — 'tropical') data.house_system (string — the system used) data.ascendant — { longitude (float), sign (string), sign_index (int 0–11), degree_in_sign (float) } data.mc — same shape as ascendant data.planets[] — 10 objects (Sun through Pluto): name (string), longitude (float), sign (string), sign_index (int 0–11) degree_in_sign (float), house (int 1–12) is_retrograde (bool), dignity (string), dignity_score (int) is_exaltation_degree (bool), dignity_disputed (bool) data.houses[] — 12 objects: house (int 1–12), cusp_longitude (float), sign (string) sign_index (int 0–11), degree_in_sign (float) data.aspects[] — each: planet_a (string), planet_b (string), type (string) exact_angle (float), orb (float), is_applying (bool) data.elements — { fire (int), earth (int), air (int), water (int), dominant (string) } data.modalities — { cardinal (int), fixed (int), mutable (int), dominant (string) } data.hemisphere — { eastern (int), western (int), northern (int), southern (int) } data.ayanamsa_value (float — 0.0 for tropical) data.ayanamsa_used (string — 'tropical') data.birth_time_provided (bool) SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable natal report. Both modes return identical underlying data. SECTION: COMPUTE CLASS MEDIUM_COMPUTE (~300ms) SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): — WesternBirthData Pydantic violations (date pattern, time pattern, lat/lon bounds) → MCP INVALID_PARAMS INVALID_PARAMS (upstream): — None expected for valid coordinates and dates post-1800. INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: — Polar latitudes (above ~65°N or below ~65°S) may cause Placidus house calculation failure; use whole_sign or equal house system for polar births. — time='00:00' accepted; lagna-sensitive results are unreliable for unknown birth times. SECTION: DO NOT CONFUSE WITH asterwise_get_natal_chart — Vedic sidereal chart using Lahiri ayanamsa; different zodiac, different house system, different planet set (9 grahas vs 10 tropical planets). asterwise_get_western_aspects — takes raw longitudes as input; use when you already have positions and don't need full chart computation.
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  • Next return chart for any planet after a given date. Finds the exact moment the specified planet returns to its natal tropical longitude and builds a complete Western natal chart for that moment at the birth location. SECTION: WHAT THIS TOOL COVERS Generalised return for any of the 10 classical tropical bodies — Mercury returns (yearly-ish), Venus (~1 year), Mars (~2 years), Jupiter (~12 years), Saturn (~29 years), through Pluto (~248 years). SECTION: WORKFLOW BEFORE: asterwise_get_western_natal. AFTER: None. SECTION: INPUT CONTRACT birth — WesternBirthData. planet — one of Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, Pluto. after_date (optional YYYY-MM-DD) — defaults to today. SECTION: OUTPUT CONTRACT Same shape as solar return: planet name, natal_longitude, return_utc, return_jd, chart SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data. SECTION: COMPUTE CLASS SLOW_COMPUTE for outer planets (Jupiter+ return can search years ahead) SECTION: ERROR CONTRACT INVALID_PARAMS (local): planet not in the valid 10-planet set → MCP INVALID_PARAMS locally. INTERNAL_ERROR: Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: Neptune return takes ~165 years — only useful for generational analysis, not individual lifetime prediction. Pluto return: ~248 years, never completes in one lifetime. SECTION: DO NOT CONFUSE WITH asterwise_get_western_solar_return — Sun-only shortcut. asterwise_get_western_lunar_return — Moon-only shortcut.
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  • Fetches an AI-synthesised Western sun-sign horoscope for a chosen horizon and returns structured guidance fields plus metadata about the model and period. SECTION: WHAT THIS TOOL COVERS Calls the upstream western horoscope service for a tropical sun sign and a period of daily, weekly, monthly, or yearly. Uses the tropical zodiac (not sidereal). Content is grounded in current sky aspects, slow planet positions, and the solar season — not Vedic transit rules. It does not compute a personal natal chart, divisional charts, or dasha — only sign-level tropical transit-flavoured copy tied to the requested horizon. No remedy field — Western tradition has no planetary remedy system. SECTION: WORKFLOW BEFORE: None — this tool is standalone. AFTER: asterwise_get_western_natal — if the user needs a personalised tropical chart beyond sign-general copy. SECTION: INPUT CONTRACT period is constrained to the tool schema enum (daily, weekly, monthly, yearly). sun_sign accepts English zodiac names only (Aries, Taurus, Gemini, Cancer, Leo, Virgo, Libra, Scorpio, Sagittarius, Capricorn, Aquarius, Pisces). No Sanskrit aliases — this is Western astrology. response_format selects JSON vs markdown rendering only. SECTION: OUTPUT CONTRACT data.content: headline (string) narrative (string) love (string) career (string) money (string) body (string) power_window (string) caution_window (string) closing_message (string) phases[] (monthly only — array of phase objects with phase_number, start_date, end_date, title, narrative) year_theme (string — yearly only) chapters[] (yearly only — array of chapter objects with chapter_number, start_date, end_date, title, narrative) auspicious_months[] (yearly only — string array of month names) landmark_dates[] (yearly only — array of {date, event} objects) data.model_used (string — AI model version label) data.generated_at (string — ISO UTC) data.period_key (string — YYYY-MM-DD for daily; YYYY-W## for weekly; YYYY-MM for monthly; YYYY for yearly) data.horizon (string — 'daily', 'weekly', 'monthly', or 'yearly') data.sun_sign (string — lowercase English, e.g. 'aries') data.zodiac_type (string — 'western') SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data — no fields are added, removed, or filtered by either mode. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): — Invalid period enum or other Pydantic field violations on the tool schema → MCP INVALID_PARAMS INVALID_PARAMS (upstream): — Unknown or unsupported sun_sign → MCP INTERNAL_ERROR at the tool layer (upstream rejection). INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR — Horoscope not yet generated for the current period → MCP INTERNAL_ERROR with status not_generated Edge cases: — Sun-sign content only; not a substitute for birth-chart analysis. — If a period's horoscope has not yet been generated by the cron, returns 404 upstream (surfaces as INTERNAL_ERROR). — No remedy field in western horoscopes by design. SECTION: DO NOT CONFUSE WITH asterwise_get_horoscope — Vedic Moon-sign horoscope using sidereal zodiac, not Western tropical sun-sign. asterwise_get_western_natal — full personalised tropical chart from birth data, not sign-general editorial copy.
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  • Lookup a specific crystal by slug or name (case-insensitive). Returns full detail including dual Vedic/Western planetary assignments, all healing properties, and any safety cautions. SECTION: WHAT THIS TOOL COVERS Returns one crystal entry from the 50-crystal database. Accepts URL-safe slugs (e.g. 'blue-sapphire', 'rose-quartz') or display names (e.g. 'Blue Sapphire', 'Rose Quartz'). The caution field carries critical safety information — Blue Sapphire and Hessonite Garnet carry CRITICAL cautions about Jyotish use without qualified practitioner assessment. Malachite has a CRITICAL toxicity caution. Always surface the caution field to end users. SECTION: WORKFLOW BEFORE: None — standalone or after asterwise_get_gemstone_recommendations. AFTER: None. SECTION: INPUT CONTRACT name: Crystal slug or display name. Examples: 'amethyst', 'blue-sapphire', 'Cat's Eye Chrysoberyl' SECTION: OUTPUT CONTRACT Same shape as each crystal in asterwise_get_crystals — full single crystal object. SECTION: RESPONSE FORMAT response_format=json — single crystal object. response_format=markdown — formatted detail card. Both return identical data. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (upstream): Unknown crystal name → 404, surfaces as MCP INTERNAL_ERROR. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_crystals — full 50-crystal catalogue. asterwise_get_crystal_by_planet — all crystals for a Vedic planet. asterwise_get_gemstone_recommendations — natal chart-based gem recommendations (house lordship rules), different from this database.
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  • Returns all crystals associated with a specific Vedic planet. Results are sorted with primary Navaratna gems first, then Uparatna substitutes. Only Navaratna and Uparatna Vedic assignments are returned — crystals with no Vedic planetary correspondence are excluded. SECTION: WHAT THIS TOOL COVERS Filters the crystal database by vedic_planet field. Only returns crystals where vedic_correspondence is 'navaratna' or 'uparatna' — none_classical crystals are not returned here because they have no actual Vedic planetary assignment. Useful for Jyotish practitioners recommending remedial gems. Navaratna gems appear first. Valid planets: Sun, Moon, Mars, Mercury, Jupiter, Venus, Saturn, Rahu, Ketu. SECTION: WORKFLOW BEFORE: RECOMMENDED — asterwise_get_natal_chart — identify the planet needing remediation. AFTER: asterwise_get_gemstone_recommendations — for chart-specific gem safety assessment. SECTION: INPUT CONTRACT planet: One of Sun, Moon, Mars, Mercury, Jupiter, Venus, Saturn, Rahu, Ketu. SECTION: OUTPUT CONTRACT data.total (int) data.crystals[] — same shape as asterwise_get_crystals, sorted Navaratna first. SECTION: RESPONSE FORMAT response_format=json — filtered crystal array. response_format=markdown — formatted list. Both return identical data. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (upstream): Unknown planet → 404. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_gemstone_recommendations — natal chart house-lordship gem recommendation with contraindications; use for actual gem prescription, not just listing. asterwise_get_crystals — all 50 crystals including Western-only ones.
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  • Lookup a specific dream symbol by slug or name (case-insensitive). Returns full dual-tradition interpretation including Jungian archetype, Vedic dream meaning with auspiciousness, context variants, and related symbols. SECTION: WHAT THIS TOOL COVERS Single symbol lookup with complete detail. Use for dream journaling apps, AI-powered dream interpretation (the themes[] field is designed for synthesis), and cross-tradition comparison. Notable tradition conflicts: Snake (Western=transformation; Vedic=partial — white snake=auspicious, black chasing=inauspicious). Elephant=auspicious both traditions (Ganesha). Crow=inauspicious both traditions (Yama's messenger). Wedding=conflict (West=union; Vedic=inauspicious). SECTION: WORKFLOW BEFORE: None — standalone. AFTER: None. SECTION: INPUT CONTRACT name: Symbol slug or display name. Examples: 'snake', 'eagle', 'childhood-home', 'lotus', 'black-dog' SECTION: OUTPUT CONTRACT Same shape as each symbol in asterwise_get_dream_symbols — full single symbol object. SECTION: RESPONSE FORMAT response_format=json — single symbol object. response_format=markdown — formatted interpretation card. Both return identical data. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (upstream): Unknown symbol → 404, surfaces as MCP INTERNAL_ERROR. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_dream_symbols — full database listing with optional category filter.
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  • Fetch SEC XBRL frames for one concept × one period across all reporting companies. Inline response returns the top N ranked companies; the full frames response (all reporters) is materialized as df_<id> when a canvas is available, queryable via secedgar_dataframe_query. Accepts friendly names like "revenue" or "assets" (discover via secedgar_search_concepts) or raw XBRL tags. One call hits one XBRL tag — when a friendly name maps to multiple same-meaning tags, the response's `unqueried_tags` lists the others; call again per tag and UNION/COALESCE in SQL with an analysis-specific priority (e.g. SalesRevenueGoodsNet is goods-only). The response's `related_tags` separately flags alternate-DEFINITION tags a meaningful share of filers use as their primary line (e.g. cash incl. restricted cash, equity incl. noncontrolling interest) — a whole-universe screen on the base tag silently omits those filers; query them separately, but do not blindly union (the semantics differ). Response includes `value_distribution` and `period_end_range` to flag XBRL scale-factor anomalies and fiscal-year mixing.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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