Cross-Venue Prediction Market Spread Monitor
Pricing
from $0.05 / actor start
Read-only, explainable Polymarket and Kalshi candidate spread analysis with fee, depth, and matching evidence.
You can access the Cross-Venue Prediction Market Spread Monitor programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.2", "x-build-id": "PixOS2wYwI4rjTsge" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/obsequious_doughnut~cross-venue-market-spread-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-obsequious_doughnut-cross-venue-market-spread-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/obsequious_doughnut~cross-venue-market-spread-monitor/runs": { "post": { "operationId": "runs-sync-obsequious_doughnut-cross-venue-market-spread-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/obsequious_doughnut~cross-venue-market-spread-monitor/run-sync": { "post": { "operationId": "run-sync-obsequious_doughnut-cross-venue-market-spread-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "Data mode", "enum": [ "fixtures", "live" ], "type": "string", "description": "Live retrieves current public market metadata and executable order books. Fixtures provides one deterministic test record.", "default": "live" }, "stakeUsd": { "title": "Analysis stake (USD)", "minimum": 0.01, "maximum": 100000, "type": "number", "description": "Total USD capital budget across both legs, including configured fees and safety buffer; no orders are placed.", "default": 100 }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of ranked candidate spread records to emit.", "default": 100 }, "minSimilarity": { "title": "Minimum title similarity", "minimum": 0.2, "maximum": 1, "type": "number", "description": "Minimum token similarity required before deeper compatibility checks.", "default": 0.55 }, "maxCloseHours": { "title": "Maximum close-time difference (hours)", "minimum": 1, "maximum": 720, "type": "number", "description": "Maximum difference between venue market close times.", "default": 72 }, "minNetReturnPct": { "title": "Minimum estimated net return (%)", "minimum": -100, "maximum": 1000, "type": "number", "description": "Only emit candidates at or above this estimated post-buffer return.", "default": 0 }, "feeRatePct": { "title": "Estimated total fee rate (%)", "minimum": 0, "maximum": 20, "type": "number", "description": "Conservative configurable estimate; confirm venue-specific fees manually.", "default": 1 }, "slippageBufferPct": { "title": "Safety buffer (%)", "minimum": 0, "maximum": 20, "type": "number", "description": "Additional percentage of modeled acquisition cost reserved as a safety margin.", "default": 0.5 }, "maxMarketsPerVenue": { "title": "Maximum markets per venue", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Hard cap on normalized active binary market metadata loaded from each venue.", "default": 3000 }, "maxSourcePages": { "title": "Maximum source pages", "minimum": 1, "maximum": 30, "type": "integer", "description": "Hard pagination cap applied independently to each venue.", "default": 30 }, "maxBookPairs": { "title": "Maximum matched pairs to hydrate", "minimum": 1, "maximum": 250, "type": "integer", "description": "Maximum plausible cross-venue pairs whose executable order books are requested.", "default": 100 }, "authorization": { "title": "Live source authorization", "type": "object", "description": "Operator data-rights attestation. The deployed Actor defaults to the permissions confirmed for this private release.", "default": { "polymarketPublicApiApproved": true, "kalshiDeveloperAgreementReviewed": true, "commercialRedistributionApproved": true, "termsReviewedOn": "2026-08-13" } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Cross-Venue Prediction Market Spread Monitor from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: