Tool search 164,478 tools · 10,067 live servers

Answers "who has filed this quarter's results, who hasn't, and what came in since last time?" — filed / not-yet lists against the statutory deadline, plus a diff of filings new since the previous publish. Built for stateless agents: polling this replaces a webhook. | "누가 냈고 누가 아직인가 · 지난번 이후 새로 뜬 건 뭔가"에 답합니다. 법정 마감 D-day 와 직전 발행 대비 신규 목록까지. 상태를 못 들고 다니는 에이전트를 위한 도구입니다.

Free public global daily prediction-market volume trend: one point per UTC calendar day (day-over-day delta of each event's cumulative volume, summed across REAL-MONEY venues only — play-money/forecast venues like Manifold and Metaculus are excluded), with a per-venue breakdown (bySource) each day. Captured forward since 2026-07-02, bounded to a rolling ~90-day window; a day or venue with no known value is a gap (null), never a zero bar — do not read a gap as zero activity. Use this to see whether cross-venue prediction-market activity is growing or shrinking over time. No API key required.

"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.

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

"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.

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

Use when a user asks for drawdowns, weak periods, best-versus-worst results, or whether a headline hides an unfavorable distribution. Returns detailed cuts of the current-rule historical replay: per calendar year, per theme, return distribution buckets, holding periods, the ten best and ten worst closed trades, the open book, and closed+open combined on identical buckets. Use `section` to pull one cut instead of all of them. Signal data, not investment advice.

Use when a user asks for stricter time-ordered evidence, weak years, benchmark underperformance, or a check against look-ahead. Returns the committed cache-frozen annual walk-forward artifact. Each year's candidate is selected using only earlier observations and then traded for the next calendar year with next-open execution and costs. Returns the content-derived evidence id, input hash manifest, aggregate results, and paged per-symbol/year rows. Weak periods and underperformance versus buy-and-hold are retained. Set artifact to 'pooled_selection' for the class-pooled selection audit (per-name and pooled rule selection both converge to the untuned class engine) or 'model_portfolio' for the monthly walk-forward of the shipped model-portfolio construction (12-1 momentum top 10/20 among engine-long quality stocks, every risk profile, benchmarks, monthly picks, broad-universe check). Historical validation, not live performance or advice.

For one live listing, find the closest calendar-confirmed stays with the same length when preferred dates do not work. Results are not priced; call get_quote for the final total.

Trip-condition board for tracked tourist spots (SF Bay Area, Napa, Monterey/Big Sur): one verdict per spot with per-factor readings. Factors per spot (only the ones that matter for that place): visibility (vision-model webcam reading), heat and cold (NWS hourly — outdoor-seating and heatwave-cancellation bands, freeze flag), wind (nearest NDBC buoy or forecast — the Big Sur sun-and-wind balance), smoke (EPA AirNow AQI — wildfire haze), alerts (NWS CAP + advisories), strikes (BART/511), road (Caltrans closures incl. SR-1/Big Sur). Pass spot_id (e.g. "golden-gate", "napa", "big-sur") for one spot plus its `week`: a 7-day forecast outlook per local calendar day (hi/lo °F, conditions, flags like "extreme heat"/"freezing"/"windy") for picking a visit day. Week rows are forecast-only; visibility/smoke/alerts are live signals and appear in `factors`. Statuses are good|caution|bad|unknown; the spot verdict is the worst non-unknown factor, and `flagged` names which factor(s) drove it. "unknown" means that feed is not reporting fresh data — an empty or stale feed shows unknown, never all-clear. Some cameras are labeled proxies in `note` (e.g. Alamo Square has no public camera facing the Painted Ladies). Thresholds documented in gateway/spots.py.

Reserve a slot and get a payment link. This is the only way to buy — there is no checkout on the website. The slot is held for 30 minutes. Confirm the exact time and the price with the buyer before calling this, and use their real email address: the calendar invitation and receipt go there. You must call list_products first, put the session options to the buyer in your own reply, and wait for them to choose. This tool needs the catalogue_token from that call and buyer_confirmed_session: true, which you may only set once the buyer has actually answered. Choosing a session on their behalf from what they said earlier is not the same as asking, and is not acceptable here. Before calling, ask the buyer what they want to discuss and what they are hoping to get out of the call, and pass their answers as topic and desired_outcome. Fifteen minutes is short; the seller uses these to prepare, and a booking that arrives blank wastes some of the time the buyer paid for.

Buy a certificate. Certificates are objects, not appointments: there is no slot, no calendar entry and no meeting. One is issued the moment payment settles, emailed as a PDF, and registered against a hash anyone can verify. Use this instead of create_order, which is only for booking time. As with sessions, show the buyer what is on offer and let them choose rather than deciding for them.

Bitcoin and Ethereum trend signal: the long-only state for each sleeve (LONG or CASH), the 50-day trend gate each trades on, and the BTC 200-day master gate that overrides both — evaluated on UTC daily closes, with price and day change. A rules-based risk-on/risk-off verdict for crypto, not raw price data. Free tier: exactly one completed UTC close behind — evaluated every calendar day, weekends included, and stamped with the close it used (signal_close_date). Live sibling on the newest close (x402, pay-per-call): get_crypto_trend_live.

get_crypto_trend on the newest completed UTC daily close — evaluated every calendar day including weekends, stamped with the close it used. The free tool is one close behind. No wallet? get_crypto_trend is free. $0.005 USDC per call (x402).

Fetch the bundled critical skill pack (regime + risk_calendar + health). Call this on every boot before any trading decisions. Returns the current market regime, known risk events in the next 14 days, and a market health score — three synthesised verdicts that every strategy depends on.

Fetch a specific Agentberg skill pack by name. Critical skills (regime, risk_calendar, health) are automatically bundled in get_skills. Optional skills: 'rotation' for sector money-flow analysis, 'narrative' for macro headline synthesis.

Call cc.economic_calendar — Upcoming high-impact macroeconomic events (CPI, FOMC, NFP, etc.) with forecast vs previous values. 60-min cache. Purpose: Upcoming high-impact macroeconomic events (CPI, FOMC, NFP, etc.) with forecast vs previous values. 60-min cache. Behavior: READ-ONLY. Does not place orders, move funds, or mutate your exchange account. Responses may be cached (~3600s). Auth: X-Api-Key or x402 payment proof (X-PAYMENT / __x_payment). Anonymous unauthenticated calls receive HTTP 402 with payment accepts. Cost: $0.001 USDC per successful call (x402 Base USDC pay-per-use or prepaid X-Api-Key balance). Linked Connect keys are free. This is billing, not a side effect. Rate limit: 60/min (per API key). Tier: standard. Returns: Array of events with dates, countries, impact level, forecast/actual/previous values. Guidelines: Use for research / signal context. Pair with cc.agent_strategy (paper) before any live order. Do not invent fills from this data alone. Tags: macro, calendar, fomc, cpi, nfp, economic.