Foresea Forecasting
Forecast future events and scan prediction-market edges.
我該用這個嗎
品質與安全性
發現項目（3）
- HIGHTool poisoning patterns detected
- LOWTool 'foresea_crypto_edge' description lacks action verb在 foresea_crypto_edge 中
- INFOTool description contains placeholder or incomplete text在 foresea_analyze_market 中
根據工具定義與協定合規性的自動化分析。
上下文成本
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高，可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案：
{
"mcpServers": {
"forecasting": {
"url": "https://foresea.ink/mcp/"
}
}
}遠端端點
https://foresea.ink/mcp/streamable-http它能做什麼
工具清單
工具（28）
🟢foresea_forecast(question, description, resolution_criteria, question_type, options, ...)
Call this whenever the user asks about probability, likelihood, or whether something will happen. Good triggers: "Will X happen?", "What are the chances of Y?", "How likely is Z?", "What's the probability that…", "Do you think X will…", "Should I bet on…". Returns a calibrated YES/NO probability (or numeric/date range) with written rationale and supporting news evidence. If you also have a market price (market_probability) or URL (market_url), pass it to get the model-vs-market edge — how mispriced the market is. Example: question="Will the Fed cut rates by March 2026?", market_probability=0.4 → {predicted_answer:"No", confidence:0.62, rationale, evidence_sources, market_analysis:{model_probability:0.54, edge:+0.14, stance:"model_above_market"}} Handles: binary YES/NO, multiple-choice, numeric ranges, and date questions.
輸入結構描述
{
"type": "object",
"properties": {
"question": {
"title": "Question",
"type": "string"
},
"description": {
"default": "",
"title": "Description",
"type": "string"
},
"resolution_criteria": {
"default": "",
"title": "Resolution Criteria",
"type": "string"
},
"question_type": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Question Type"
},
"options": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Options"
},
"categories": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Categories"
},
"variant": {
"default": "variant0_neutral_baseline",
"title": "Variant",
"type": "string"
},
"attach_evidence": {
"default": true,
"title": "Attach Evidence",
"type": "boolean"
},
"evidence_top_k": {
"default": 5,
"title": "Evidence Top K",
"type": "integer"
},
"market_platform": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Market Platform"
},
"market_url": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Market Url"
},
"market_outcome": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Market Outcome"
},
"market_probability": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Market Probability"
}
},
"required": [
"question"
],
"title": "foresea_forecastArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_forecastOutput"
}🟢foresea_analyze_market(question, platform, slug, market_id, ticker, ...)
Call this when the user mentions a specific prediction market by URL, slug, or ticker — or asks whether a particular market is over/underpriced. Good triggers: "Is this Polymarket fair?", "What's the edge on kalshi:XXXXX?", "Should I buy/sell this market?", user pastes a Polymarket or Kalshi URL. Fetches the live price, gathers evidence, forecasts, computes model-vs-market edge, and returns a recommendation. Use foresea_forecast instead when there is no specific live market — just a general probability question. Example: platform="polymarket", slug="fed-rate-cut-march-2026" → {model_probability, market_probability, edge, stance, recommendation, thesis}.
輸入結構描述
{
"type": "object",
"properties": {
"question": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Question"
},
"platform": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Platform"
},
"slug": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Slug"
},
"market_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Market Id"
},
"ticker": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Ticker"
},
"market_probability": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Market Probability"
},
"variant": {
"default": "variant0_neutral_baseline",
"title": "Variant",
"type": "string"
},
"evidence_top_k": {
"default": 5,
"title": "Evidence Top K",
"type": "integer"
},
"skills": {
"anyOf": [
{
"items": {
"additionalProperties": {
"type": "string"
},
"type": "object"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Skills"
},
"builtin_skills": {
"default": false,
"title": "Builtin Skills",
"type": "boolean"
},
"ground_in_record": {
"default": false,
"title": "Ground In Record",
"type": "boolean"
},
"tool_loop": {
"default": false,
"title": "Tool Loop",
"type": "boolean"
},
"max_tool_steps": {
"default": 5,
"title": "Max Tool Steps",
"type": "integer"
}
},
"title": "foresea_analyze_marketArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_analyze_marketOutput"
}🟢foresea_scan_markets(platform, limit, min_edge, evidence_top_k, query)
Call this when the user wants to find mispriced or interesting markets, not evaluate a specific one. Good triggers: "What should I bet on?", "Find me trading opportunities", "Which markets are mispriced right now?", "What's Foresea's best edge today?", "Scan Polymarket for opportunities". Returns markets ranked by model-vs-market disagreement, each with model probability, market price, and edge. For a specific market, use foresea_analyze_market instead. Example: platform="kalshi", min_edge=0.1 → [{question, market_probability, model_probability, edge, market_url}].
輸入結構描述
{
"type": "object",
"properties": {
"platform": {
"default": "polymarket",
"title": "Platform",
"type": "string"
},
"limit": {
"default": 4,
"title": "Limit",
"type": "integer"
},
"min_edge": {
"default": 0.1,
"title": "Min Edge",
"type": "number"
},
"evidence_top_k": {
"default": 3,
"title": "Evidence Top K",
"type": "integer"
},
"query": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Query"
}
},
"title": "foresea_scan_marketsArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_scan_marketsOutput"
}🟢foresea_batch_quotes(refs)
Call this when the user wants current price/volume for several markets at once -- a watchlist, a portfolio, "check on these 5 markets" -- instead of calling foresea_analyze_market once per market. Each ref is "platform:ident", e.g. "kalshi:KXFED-25JUN-H" or "polymarket:some-market-slug". Every quote carries fetched_at and age_seconds so you can judge freshness yourself -- both venues rate-limit hard, so don't assume a quote is live without checking age_seconds. One bad ref returns an error on that entry only; the rest of the batch still succeeds. Up to 50 refs per call. Example: refs=["kalshi:KXFED-25JUN-H", "polymarket:fed-cut-2026"] → {quotes: [{platform, ident, probability, volume, fetched_at, age_seconds, error}], count, truncated}.
輸入結構描述
{
"type": "object",
"properties": {
"refs": {
"items": {
"type": "string"
},
"title": "Refs",
"type": "array"
}
},
"required": [
"refs"
],
"title": "foresea_batch_quotesArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_batch_quotesOutput"
}🟢foresea_check_run(client_run_key)
Call this after foresea_analyze_market timed out or errored with a message naming a client_run_key -- the research it started may still be running server-side. Returns {"status": "running", ...} if it's not done yet (call again in a bit), or the full report once it is. Do not call this speculatively; only use the client_run_key a prior foresea_analyze_market call actually gave you. Example: client_run_key="a1b2c3..." → {status:"running", id:"agent_run_..."} or the full report once complete.
輸入結構描述
{
"type": "object",
"properties": {
"client_run_key": {
"title": "Client Run Key",
"type": "string"
}
},
"required": [
"client_run_key"
],
"title": "foresea_check_runArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_check_runOutput"
}🟢foresea_track_record(fields)
Call this when the user asks how reliable or accurate Foresea is, or wants to know whether to trust a forecast. Good triggers: "How good is Foresea?", "What's the track record?", "Has it been right before?", "Is it calibrated?", "What's the Brier score?". Returns accuracy, Brier score, calibration (ECE), and skill-vs-market broken down by time horizon. Pass optional fields list (e.g. ['brier_score', 'accuracy', 'n_snapshots_resolved']) to reduce token usage.
輸入結構描述
{
"type": "object",
"properties": {
"fields": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Fields"
}
},
"title": "foresea_track_recordArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_track_recordOutput"
}⚪foresea_edge_board(limit, min_edge, fields, cursor)
Call this when the user wants the current top trading opportunities with explicit trade directions and historical backing. Good triggers: "What are the best bets right now?", "Show me the edge board", "Which model is winning the paper-trading competition?", "What's the strongest edge today?", "Are these edges statistically significant?". Returns open markets ranked by model-vs-market disagreement, each with Buy YES/NO direction, implied odds, whether the edge is historically significant, and a multi-model comparison. Supports cursor pagination, limit, min_edge threshold, and field masking.
輸入結構描述
{
"type": "object",
"properties": {
"limit": {
"default": 20,
"title": "Limit",
"type": "integer"
},
"min_edge": {
"default": 0,
"title": "Min Edge",
"type": "number"
},
"fields": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Fields"
},
"cursor": {
"default": 0,
"title": "Cursor",
"type": "integer"
}
},
"title": "foresea_edge_boardArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_edge_boardOutput"
}🟡foresea_venue_data(platform, operation, parameters, body)
Read public historical markets/candles/trades, batch books/midpoints/spreads, fees, holders, open interest, event volume, milestones and weather. Omit operation to discover operation names and schemas. No account or write access.
輸入結構描述
{
"type": "object",
"properties": {
"platform": {
"default": "",
"title": "Platform",
"type": "string"
},
"operation": {
"default": "",
"title": "Operation",
"type": "string"
},
"parameters": {
"anyOf": [
{
"additionalProperties": true,
"type": "object"
},
{
"type": "null"
}
],
"default": null,
"title": "Parameters"
},
"body": {
"anyOf": [
{
"items": {
"additionalProperties": true,
"type": "object"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Body"
}
},
"title": "foresea_venue_dataArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_venue_dataOutput"
}🟢foresea_exchange_status
Call this to check Kalshi exchange operational status (trading active flag) and operational hours/schedule.
輸入結構描述
{
"type": "object",
"properties": {},
"title": "foresea_exchange_statusArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_exchange_statusOutput"
}🟢foresea_orderbook(ticker_or_token, platform)
Call this to fetch the live bids and asks orderbook depth for a Kalshi market ticker (e.g. 'KXFED-25JUN-H') or Polymarket YES-token ID.
輸入結構描述
{
"type": "object",
"properties": {
"ticker_or_token": {
"title": "Ticker Or Token",
"type": "string"
},
"platform": {
"default": "",
"title": "Platform",
"type": "string"
}
},
"required": [
"ticker_or_token"
],
"title": "foresea_orderbookArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_orderbookOutput"
}⚪foresea_market_tags
Call this to sample Polymarket's category vocabulary. Each entry is a label and the slug that identifies it. This is one page of at most 100 tags, not the full taxonomy: Polymarket has tens of thousands, and the endpoint returns a fixed slice that is ordered neither alphabetically nor by market activity. So absence here does not mean a tag is unused, presence does not mean it is active, and some entries are one-off or misspelled. Treat it as a vocabulary sample, not a classification the markets are organised by.
輸入結構描述
{
"type": "object",
"properties": {},
"title": "foresea_market_tagsArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"items": {
"additionalProperties": true,
"type": "object"
},
"title": "Result",
"type": "array"
}
},
"required": [
"result"
],
"title": "foresea_market_tagsOutput"
}🟢foresea_price_history(ticker_or_market, series_ticker)
Call this to retrieve historical price series or OHLC candlesticks for a market (e.g. Kalshi ticker or Polymarket token/slug).
輸入結構描述
{
"type": "object",
"properties": {
"ticker_or_market": {
"title": "Ticker Or Market",
"type": "string"
},
"series_ticker": {
"default": "",
"title": "Series Ticker",
"type": "string"
}
},
"required": [
"ticker_or_market"
],
"title": "foresea_price_historyArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"items": {
"additionalProperties": true,
"type": "object"
},
"title": "Result",
"type": "array"
}
},
"required": [
"result"
],
"title": "foresea_price_historyOutput"
}🟢foresea_live_data(event_ticker, data_type, milestone_id)
Call this to fetch real-time sports game statistics, play-by-play data, and live event feeds from Kalshi. Provide event_ticker for event charts, or milestone_id with data_type="game_stats" for play-by-play.
輸入結構描述
{
"type": "object",
"properties": {
"event_ticker": {
"default": "",
"title": "Event Ticker",
"type": "string"
},
"data_type": {
"default": "",
"title": "Data Type",
"type": "string"
},
"milestone_id": {
"default": "",
"title": "Milestone Id",
"type": "string"
}
},
"title": "foresea_live_dataArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_live_dataOutput"
}🟢foresea_polymarket_meta(target, market_id)
Call this to fetch Polymarket metadata: event series listings, community discussion comments for a market, or sports league metadata (target: 'series', 'comments', 'sports', 'teams'). 'series' lists the series and how many events each holds, not the events themselves -- fetch a series by slug for those. 'sports' lists every league with the ids that link it to other tools, not league artwork or homepages. 'comments' gives the comment, its author address and its reaction count, not the commenters' profiles or individual reactions.
輸入結構描述
{
"type": "object",
"properties": {
"target": {
"default": "series",
"title": "Target",
"type": "string"
},
"market_id": {
"default": "",
"title": "Market Id",
"type": "string"
}
},
"title": "foresea_polymarket_metaArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"items": {
"additionalProperties": true,
"type": "object"
},
"title": "Result",
"type": "array"
}
},
"required": [
"result"
],
"title": "foresea_polymarket_metaOutput"
}🟢foresea_recent_trades(platform, ticker_or_token, limit)
Call this to fetch recent public executed trades / trade tape (prices, sizes, timestamps) on Kalshi or Polymarket.
輸入結構描述
{
"type": "object",
"properties": {
"platform": {
"default": "kalshi",
"title": "Platform",
"type": "string"
},
"ticker_or_token": {
"default": "",
"title": "Ticker Or Token",
"type": "string"
},
"limit": {
"default": 20,
"title": "Limit",
"type": "integer"
}
},
"title": "foresea_recent_tradesArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"items": {
"additionalProperties": true,
"type": "object"
},
"title": "Result",
"type": "array"
}
},
"required": [
"result"
],
"title": "foresea_recent_tradesOutput"
}🟢foresea_market_leaderboard(limit)
Call this to fetch the top profitable prediction market trader leaderboard and rankings from Polymarket.
輸入結構描述
{
"type": "object",
"properties": {
"limit": {
"default": 20,
"title": "Limit",
"type": "integer"
}
},
"title": "foresea_market_leaderboardArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"items": {
"additionalProperties": true,
"type": "object"
},
"title": "Result",
"type": "array"
}
},
"required": [
"result"
],
"title": "foresea_market_leaderboardOutput"
}⚪foresea_debate_market(question, platform, market_probability, resolution_criteria)
Conduct an adversarial multi-agent debate (Bull vs. Bear vs. Chief Risk Judge) to cross-examine evidence and isolate blind spots on a forecasting question.
輸入結構描述
{
"type": "object",
"properties": {
"question": {
"title": "Question",
"type": "string"
},
"platform": {
"default": "Market",
"title": "Platform",
"type": "string"
},
"market_probability": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Market Probability"
},
"resolution_criteria": {
"default": "",
"title": "Resolution Criteria",
"type": "string"
}
},
"required": [
"question"
],
"title": "foresea_debate_marketArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_debate_marketOutput"
}🟢foresea_optimize_portfolio(bankroll_usd, kelly_fraction, min_edge)
Calculate optimal mathematical Fractional Kelly capital allocations and position sizes across live Grade A/B prediction market opportunities.
輸入結構描述
{
"type": "object",
"properties": {
"bankroll_usd": {
"default": 1000,
"title": "Bankroll Usd",
"type": "number"
},
"kelly_fraction": {
"default": 0.25,
"title": "Kelly Fraction",
"type": "number"
},
"min_edge": {
"default": 0.05,
"title": "Min Edge",
"type": "number"
}
},
"title": "foresea_optimize_portfolioArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_optimize_portfolioOutput"
}🟢foresea_feed_latest(limit, min_edge)
Fetch the real-time unified Foresea Alpha & Agent Feed, combining live prediction market edge signals, autonomous agent trades & theses, and leaderboard standings.
輸入結構描述
{
"type": "object",
"properties": {
"limit": {
"default": 10,
"title": "Limit",
"type": "integer"
},
"min_edge": {
"default": 0.05,
"title": "Min Edge",
"type": "number"
}
},
"title": "foresea_feed_latestArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_feed_latestOutput"
}⚪foresea_weather_radar(target_date)
Scan live temperature and weather prediction markets (Kalshi KXHIGHNY, KXHIGHCHI, KXHIGHMIA, KXHIGHAUS, KXHIGHDEN, KXHIGHPHIL, etc.) against neural weather models (Google DeepMind WeatherNext 3 / MetNet) and high-resolution multi-model ensembles, calibrated with station microclimate bias profiles. Returns ranked mispricings, strike bracket probabilities, and model-vs-market edge.
輸入結構描述
{
"type": "object",
"properties": {
"target_date": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Target Date"
}
},
"title": "foresea_weather_radarArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_weather_radarOutput"
}🟢foresea_weather_forecast(station_or_query, target_date)
Retrieve neural model weather forecasts (Google Maps Weather API / WeatherNext 3 / MetNet, ECMWF, GFS, GraphCast) with empirical station bias correction (e.g. KNYC Central Park, KMDW Chicago Midway, KDEN Denver) and strike bracket probability calculations for weather prediction markets.
輸入結構描述
{
"type": "object",
"properties": {
"station_or_query": {
"title": "Station Or Query",
"type": "string"
},
"target_date": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Target Date"
}
},
"required": [
"station_or_query"
],
"title": "foresea_weather_forecastArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_weather_forecastOutput"
}🟡foresea_batch_forecast(questions, items, concurrency_limit, variant, attach_evidence, ...)
Submit up to 25 forecasting questions concurrently and receive structured predictions with confidence probabilities, bull/bear factor decomposition, key catalysts, and evidence citations for each question.
輸入結構描述
{
"type": "object",
"properties": {
"questions": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Questions"
},
"items": {
"anyOf": [
{
"items": {
"additionalProperties": true,
"type": "object"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Items"
},
"concurrency_limit": {
"default": 5,
"title": "Concurrency Limit",
"type": "integer"
},
"variant": {
"default": "variant0_neutral_baseline",
"title": "Variant",
"type": "string"
},
"attach_evidence": {
"default": true,
"title": "Attach Evidence",
"type": "boolean"
},
"evidence_top_k": {
"default": 3,
"title": "Evidence Top K",
"type": "integer"
}
},
"title": "foresea_batch_forecastArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_batch_forecastOutput"
}⚪foresea_crypto_edge(min_edge, limit)
Scan real-time Kalshi cryptocurrency prediction markets (KXBTCD threshold contracts) scored against Black-Scholes zero-drift diffusion models and spot volatility. Returns tradeable market mispricings, implied odds, calibration reliability, and realized paper equity curves.
輸入結構描述
{
"type": "object",
"properties": {
"min_edge": {
"default": 0,
"title": "Min Edge",
"type": "number"
},
"limit": {
"default": 20,
"title": "Limit",
"type": "integer"
}
},
"title": "foresea_crypto_edgeArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_crypto_edgeOutput"
}⚪foresea_webhook_subscribe(url, events, min_edge)
Subscribe an external agent HTTP callback webhook to receive real-time dispatches for new forecasts and market edge opportunities. The response contains an HMAC secret (X-Foresea-Signature) for validating incoming payloads.
輸入結構描述
{
"type": "object",
"properties": {
"url": {
"title": "Url",
"type": "string"
},
"events": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Events"
},
"min_edge": {
"default": 0.05,
"title": "Min Edge",
"type": "number"
}
},
"required": [
"url"
],
"title": "foresea_webhook_subscribeArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_webhook_subscribeOutput"
}🟢foresea_trade_account_status
Check real prediction-market trading readiness, max order notional limits, and venue configuration statuses for Kalshi and Polymarket.
輸入結構描述
{
"type": "object",
"properties": {},
"title": "foresea_trade_account_statusArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_trade_account_statusOutput"
}⚪foresea_preview_order(platform, action, outcome, price, quantity, ...)
Validate, normalize, and simulate guardrail checks for a real Kalshi or Polymarket order without submitting it to the exchange.
輸入結構描述
{
"type": "object",
"properties": {
"platform": {
"title": "Platform",
"type": "string"
},
"action": {
"title": "Action",
"type": "string"
},
"outcome": {
"title": "Outcome",
"type": "string"
},
"price": {
"title": "Price",
"type": "number"
},
"quantity": {
"title": "Quantity",
"type": "number"
},
"order_type": {
"default": "limit",
"title": "Order Type",
"type": "string"
},
"ticker": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Ticker"
},
"slug": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Slug"
},
"token_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Token Id"
},
"time_in_force": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Time In Force"
},
"post_only": {
"default": false,
"title": "Post Only",
"type": "boolean"
}
},
"required": [
"platform",
"action",
"outcome",
"price",
"quantity"
],
"title": "foresea_preview_orderArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_preview_orderOutput"
}🟡foresea_place_order(platform, action, outcome, price, quantity, ...)
Submit a guarded real order to Kalshi or Polymarket. Live execution requires confirmation='PLACE REAL ORDER' and execute=True, and is protected by server notional ceilings and exchange guardrails.
輸入結構描述
{
"type": "object",
"properties": {
"platform": {
"title": "Platform",
"type": "string"
},
"action": {
"title": "Action",
"type": "string"
},
"outcome": {
"title": "Outcome",
"type": "string"
},
"price": {
"title": "Price",
"type": "number"
},
"quantity": {
"title": "Quantity",
"type": "number"
},
"confirmation": {
"title": "Confirmation",
"type": "string"
},
"execute": {
"default": true,
"title": "Execute",
"type": "boolean"
},
"order_type": {
"default": "limit",
"title": "Order Type",
"type": "string"
},
"ticker": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Ticker"
},
"slug": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Slug"
},
"token_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Token Id"
},
"time_in_force": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Time In Force"
},
"post_only": {
"default": false,
"title": "Post Only",
"type": "boolean"
},
"client_order_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Client Order Id"
}
},
"required": [
"platform",
"action",
"outcome",
"price",
"quantity",
"confirmation"
],
"title": "foresea_place_orderArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_place_orderOutput"
}🔴foresea_cancel_order(order_id, platform, ticker)
Cancel an active open order on Kalshi or Polymarket using its venue order ID.
輸入結構描述
{
"type": "object",
"properties": {
"order_id": {
"title": "Order Id",
"type": "string"
},
"platform": {
"default": "kalshi",
"title": "Platform",
"type": "string"
},
"ticker": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Ticker"
}
},
"required": [
"order_id"
],
"title": "foresea_cancel_orderArguments"
}輸出結構描述
{
"type": "object",
"properties": {
"result": {
"additionalProperties": true,
"title": "Result",
"type": "object"
}
},
"required": [
"result"
],
"title": "foresea_cancel_orderOutput"
}社群
證據