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261,244 tools. Last updated 2026-07-05 12:05

"Sky" matching MCP tools:

  • Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.
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  • Current sky positions vs natal chart for a single day. Returns all 10 planets with tropical longitudes and active aspects to natal positions using transit orbs: major 3°, sextile 2°, minor 1°. Provide start_date for a specific day; defaults to today. SECTION: WHAT THIS TOOL COVERS Single-day transit snapshot: where each planet is now versus where each natal planet was at birth, with applying/separating transit-to-natal aspects using tighter transit orbs than natal chart orbs. Excludes progressions and solar arc — pure transit ephemeris. SECTION: WORKFLOW BEFORE: asterwise_get_western_natal — establish natal chart first. AFTER: asterwise_get_western_transits_weekly — for week view. SECTION: INPUT CONTRACT birth — WesternBirthData (date, time, lat, lon, timezone). house_system ignored for this endpoint. start_date (optional YYYY-MM-DD) — defaults to today. SECTION: OUTPUT CONTRACT data.date, data.transit_planets[] — name, longitude, sign, is_retrograde, aspects_to_natal[] data.aspects[] — transit_planet, natal_planet, type, orb, is_applying data.total_aspects 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 MEDIUM_COMPUTE (~400ms) SECTION: ERROR CONTRACT INVALID_PARAMS (local): WesternBirthData validation failures. INTERNAL_ERROR: Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: Transit orbs are smaller than natal orbs: major 3°, sextile 2°, minor 1°. SECTION: DO NOT CONFUSE WITH asterwise_get_western_transits_weekly — 7 days vs 1 day. asterwise_get_western_transits_monthly — 30-day window vs single day.
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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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  • "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.
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  • "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).
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  • "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.
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  • Live ski snow, multi-model forecasts, powder rankings & a grounded Answer Engine for 500+ resorts.

  • 34-tool Caelus MCP for validated astrology: charts, transits, Vedic, facts, sky view, synthetic.

  • 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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  • Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).
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  • Edits an existing image guided by a text prompt. Pass a public `imageUrl` plus a `prompt` describing the change ("add a moon to the sky", "swap the background for a neon city", "make it look like a comic panel"). Submits, polls, and returns the edited image URL(s). Default model is 'grok-imagine-i2i' (6 cr per call, returns 2 variations, ~30s, best cost-to-quality on standard edits). Other I2I-capable models: 'seedream-v4-edit', 'wan-2.5-spicy-i2i', 'flux-kontext-pro', 'qwen-image-edit', 'gpt-image-1.5-i2i' (slow, ~5min). Use list_image_models for full lineup. Note: source URLs with spaces or parentheses may fail upstream; prefer clean URLs. ## Model selection guide for edits Default: `grok-imagine-i2i` (6 cr per call, returns 2 variations = 3 cr/image effective, fast ~30s, strong general-purpose edit quality). Pick a different model when: - Need a single deterministic output, or 4K resolution -> `seedream-v4-edit` (7 cr per image, supports 1K/2K/4K, multi-image up to 6) - Subtle edits / preserve composition / character consistency -> `flux-kontext-pro` or `flux-kontext-max` - NSFW edits -> `wan-2.5-spicy-i2i` - Highest quality, time is not a concern (~5 min OK) -> `gpt-image-1.5-i2i` or `grok-imagine-quality-i2i` (16 cr @ 1K, 22 cr @ 2K) - Stylized / artistic transformation -> `midjourney-i2i` If the user simply says "edit this image" with no other signal, default to `grok-imagine-i2i`.
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  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1242 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 4,774 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Expect 15-60s.
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  • Save a resort to the signed-in user's favorites. Requires a SnowSure user access token (OAuth). The slug must be a real SnowSure resort.
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  • Complete the trip: from a resort, find the nearest gateway airport(s) and get flight-search links from your home airport. The "get there" leg of the funnel — pair with find_best_powder / find_powder_trips (find fresh snow) → this → book_lodging (stay). Args: resort (slug, required — use search_resorts to resolve a name), optional origin (your home-airport IATA like DEN, or a city name).
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  • Computes KP ruling planets for the instantaneous chart at lat/lon with no birth data and returns day lord, Moon/Ascendant lord chains, and a deduplicated ruling_planets list. SECTION: WHAT THIS TOOL COVERS Current-moment KP snapshot: target_utc, day_lord, Moon and Ascendant tuples with sign/nakshatra/sub lords, ruling_planets[] unique names. Not natal positions (asterwise_get_kp_chart) and not house significators (asterwise_get_kp_significators). Coordinate sanity is upstream — not locally validated floats beyond whatever FastMCP passes. SECTION: WORKFLOW BEFORE: None — this tool is standalone. AFTER: asterwise_get_kp_chart — if natal confirmation is needed afterwards. SECTION: INPUT CONTRACT lat and lon only; no date parameter — "now" is implicit on the server clock. SECTION: OUTPUT CONTRACT data.ayanamsa (string — 'kp') data.target_utc (string — ISO UTC) data.day_lord (string — planet name) data.moon: longitude (float) rashi (string) sign_lord (string) nakshatra_lord (string) sub_lord (string) data.ascendant — same fields as data.moon data.ruling_planets[] (string array — unique names, deduplicated) 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): None — lat/lon not range-checked locally. INVALID_PARAMS (upstream): — None — coordinate errors surface as MCP INTERNAL_ERROR at the tool layer. INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: — Represents instantaneous sky — differs from natal stored charts. SECTION: DO NOT CONFUSE WITH asterwise_get_kp_chart — needs BirthData and returns full natal KP cusps. asterwise_get_prashna_chart — horary keyword workflow, not ruling-planet snapshot.
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  • Secondary progressed chart using the day-for-a-year method. Each day after birth symbolises one year of life (1 ephemeris day = 1 tropical year = 365.2421904 days). Returns all 10 progressed planet positions, progressed Ascendant and MC, and the solar arc. SECTION: WHAT THIS TOOL COVERS Secondary directions: Moon advances ~12°/year of life, Mercury/Venus track close to Sun speed, outer planets crawl. Includes progressed lunation phases internally. SECTION: WORKFLOW BEFORE: asterwise_get_western_natal. AFTER: asterwise_get_western_solar_arc — compare uniform arc vs individual motion. SECTION: INPUT CONTRACT birth — WesternBirthData. target_date (optional YYYY-MM-DD) — the date to progress to. Defaults to today. SECTION: OUTPUT CONTRACT data.target_date, data.progressed_jd, data.age_years data.solar_arc (float — ~1° per year) data.natal_sun_longitude, data.progressed_sun_longitude data.progressed_planets[] — 10 objects: name, longitude, sign, degree_in_sign, is_retrograde, dignity, dignity_score data.progressed_ascendant, data.progressed_ascendant_sign data.progressed_mc, data.progressed_mc_sign 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 MEDIUM_COMPUTE (~400ms) SECTION: ERROR CONTRACT INVALID_PARAMS (local): WesternBirthData validation failures. INTERNAL_ERROR: Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: Progressed ASC uses the actual house calculation at progressed JD (not solar arc approximation) for higher accuracy. Progressed MC uses natal MC + solar arc. SECTION: DO NOT CONFUSE WITH asterwise_get_western_solar_arc — all planets move by one uniform arc. asterwise_get_western_transits_daily — real-time sky, not symbolic progression.
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  • Render an SVG chart from EPW data. Eight chart types: `diurnal` (~10 KB, monthly hourly profile), `temp_carpet` (heatmap of hour × day-of-year — ~30 KB preview / ~150 KB full), `wind_rose` (~12 KB, polar bars by direction × speed), `monthly_boxplot` (~6 KB, Q1/median/Q3 + whiskers per month), `utci_carpet` (~90 KB, outdoor heat-stress hour × day, colored by UTCI category — Bröde 2012, shaded Tmrt), `economizer_carpet` (~90 KB, air-side economizer free / integrated / locked-out hour × day under ASHRAE 90.1 high-limit), `pv_tilt_azimuth` (~60 KB, annual PV generation across full tilt × azimuth space, isotropic-sky POA at lat from EPW header — optimum orientation marked), `solar_under_events` (~12 KB, weekly GHI of the modified scenario vs the no-overlay reference; bands color event-affected weeks. Requires `config` — server runs the pipeline twice, with and without overlays), `comparison` (~10 KB, design-condition deltas across EPWs). Accepts `url` (single), `urls` (2+ for comparison), or `config` (synthesize on the fly). Config mode is anon-safe — runs pipeline, returns SVG only. No auth required. **Token budget**: SVGs are returned inline by default. Large outputs (>50 KB) auto-upload to Blob storage (when configured) and return a URL instead, keeping your context lean. Always check `svg_size_kb` in the response. **Presentation: when handing the chart to the user, just link or embed it — don't narrate what's in it. Let the chart speak.**
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  • "What's the ticker for…" / "find the CIK for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" — resolve a user-spoken NAME to the canonical/official identifier other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (returns ticker + 10-digit CIK + company_name from SEC EDGAR + pipeworx://edgar/company/{cik} citation URI; accepts ticker, CIK, or company name as input — auto-disambiguated), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/{rxcui} citation; accepts brand or generic name). Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.
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  • Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).
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  • Edge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: days (lookback, default 14, max 30), window (snapshot family, default "1wk"). RESPONSE: tracked[] = every opportunity in the LATEST snapshot with its full edge_pp_net time-series across prior snapshots, first_seen, trend (new | widening | stable | decaying) and decay_pp_per_day (both computed on |edge_pp_net| — the value itself is signed by trade direction, negative = SELL YES); expired[] = opportunities that appeared in earlier snapshots but are GONE from the latest (closed, resolved, or arbed away) with their lifespan_days — the median lifespan is your competition clock; snapshot_dates[] = which days actually have data (snapshots are written when polymarket_edges runs on a cache-miss, so gaps mean nobody scanned that day). LIMITS: history depth is bounded by the 60-day snapshot TTL and starts from when snapshotting was enabled; decay numbers come from daily closes of edge_pp_net (net of default slippage), not intraday.
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  • The sky at a moment and place — not tied to any person. Use for "what's the sky/transits right now" or the chart of a non-birth event. Date defaults to now; lat/lon default to 0,0 (geocentric on the equator at the prime meridian), where houses and ASC/MC are nominal — pass a real location if houses matter. For a specific person's birth chart use natal_chart instead. Returns positions, houses, retrogrades, aspects.
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  • Where the visible bodies land in a framed photo of the sky, for an image prompt. Give a place, a moment, an aim (compass direction and altitude), a lens, and an image size; get each in-frame body's pixel position, apparent size, brightness, the Moon's phase orientation, a sky-state summary (twilight, limiting magnitude, horizon row), the bright bodies just outside the frame, a ready-to-use prompt, and a machine-readable `renderPlan` (a body-free background-plate prompt plus the computed layers to composite locally, for a hybrid render pipeline). Caelus computes the geometry and photometry; it does NOT render the image. For "at sunset", first find the set time with sky_events, then pass it as date.
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