# Earnings Call Transcript API - SEC 8-K Filings Parser & Monitor (`johnvc/earnings-call-transcript-api`) Actor Speaker-tagged earnings call transcripts with Q\&A pairs, plus SEC 8-K filings parsed from EDGAR: item codes, press releases, guidance sentences, sentiment. Full-text keyword search across all US filers. Pay-per-result, no start fee. - **URL**: https://apify.com/johnvc/earnings-call-transcript-api.md - **Developed by:** [John](https://apify.com/johnvc) (community) - **Categories:** AI, Developer tools, Business - **Stats:** 4 total users, 2 monthly users, 98.1% runs succeeded, 1 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $0.10 / 1,000 record returneds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Earnings Call Transcript API - SEC 8-K Filings Parser & Monitor Get earnings call transcripts with per-speaker tagging and separated Q&A, plus SEC 8-K filings parsed item by item from EDGAR, as clean structured JSON. One API covers both the words executives said on the call and the material events they filed with the SEC. Pay-per-result with no start fee and no subscription. A low-cost structured alternative to expensive market data subscriptions that return transcripts as one raw text blob and filings as bare links. ### What you get **Earnings call transcripts** (structured, not a text blob): - Every speaker turn tagged with name, role, and role type (executive, analyst, operator) - Prepared remarks separated from the Q&A session - Q&A pairs: each analyst question matched with the management answers that follow, with analyst firm affiliations - Call participants roster, fiscal quarter, call date, word and question counts - Guidance sentences extracted from executive speech - Finance-dictionary sentiment scores (positive, negative, uncertainty, net) **SEC 8-K filings** (parsed, not just linked): - Full item-code classification across the complete 8-K item map, 1.01 through 9.01: earnings (2.02), executive changes (5.02), cybersecurity incidents (1.05), bankruptcies (1.03), M&A (1.01, 2.01), and every other item - Per-item parsed text from the primary document - Press release exhibits (EX-99.1) parsed into headline, outlook section, and body - Guidance sentence extraction with quantity and period matching, so generic optimism is filtered out - EDGAR acceptance timestamps for latency-sensitive event studies - Direct EDGAR links to the filing index, primary document, and press release **Full-text keyword search**: search any word or phrase across 8-K filings from ALL US companies (for example "guidance withdrawal", "material weakness", "going concern") with date and item filters. **Monitoring mode**: turn on `onlyNew` with a schedule and each run emits only newly filed 8-Ks and newly published transcripts. A `metadataOnly` cheap mode powers lightweight alerting. ### What you do NOT get - No audio and no real-time streaming of live calls. Transcripts typically appear within hours of the call. - Transcript coverage spans roughly 1,000 to 1,500 mostly large and mid cap US companies per earnings quarter, with an archive back to about 2007. Every US filer's 8-Ks are covered, but not every micro cap has a transcript. - Sentiment scores come from a deterministic finance-domain dictionary, not an LLM. Reproducible and fast, but not a language-model judgment. - No 10-K or 10-Q financial statements and no XBRL fundamentals. This actor is about 8-K events and earnings calls. ### Use cases - **LLM training and RAG pipelines**: export clean question-answer pairs and speaker-tagged remarks, ready for fine-tuning and retrieval corpora. - **Event-driven trading research**: track 8-K item codes with acceptance timestamps, e.g. earnings releases (Item 2.02) or executive departures (Item 5.02), the moment EDGAR disseminates them. - **Guidance monitoring**: extract forward-looking sentences from press releases and calls for a watchlist, and diff them quarter over quarter. - **Cross-market screening**: full-text search every US filer's 8-Ks for crisis language such as "going concern" or "restatement". - **Compliance and IR competitive tracking**: follow what peer companies file and say, in a machine-readable format. ### When to use this actor | | This actor | Typical market data APIs | |---|---|---| | Earnings transcripts | Speaker-tagged turns, Q&A pairs, roles | Often one raw text blob, or gated to a top tier (FMP transcripts are Ultimate-only at $149/mo billed annually) | | 8-K filings | Parsed items, press release text, guidance, sentiment | Usually metadata and links only | | Filing search | Full-text across all US filers | Often a separate product (sec-api.io starts at $49/mo) | | Pricing | Pay-per-result, no start fee, no subscription | $49 to $149+ per month, annual commitments | | Structure for AI agents | JSON records, MCP-ready | Varies | If you need every ticker's transcript back to the 1990s or real-time call audio, a premium vendor is the right tool. For structured transcripts and parsed filings on demand, this actor does it for a fraction of a cent per record. ### Pricing One event, charged per record returned: a parsed 8-K filing or a structured transcript. Error rows are never charged. There is no start fee and no separate subscription. Worked example: 100 records cost about one cent. A quarterly refresh of a 50-ticker watchlist (one earnings 8-K plus one transcript each) is 100 records. ### Input | Field | Type | Required | Default | Notes | |---|---|---|---|---| | `tickers` | array | one of tickers / searchKeyword | `["AAPL"]` | Stock symbols or CIK numbers | | `dataType` | enum | yes | `both` | `filings`, `transcripts`, or `both` | | `filingsLimit` | integer | no | 10 | Max 8-K filings per ticker (1-200); caps total results in keyword mode | | `transcriptsLimit` | integer | no | 4 | Max transcripts per ticker (1-40), newest first | | `searchKeyword` | string | one of tickers / searchKeyword | - | Full-text search across ALL US filers; treats dataType as `filings` | | `eventCategories` | array | no | - | Shortcuts like `earnings`, `executive_changes`, `cybersecurity` that map to item codes | | `itemCodes` | array | no | - | Exact 8-K item codes, e.g. `["2.02"]` | | `dateFrom` / `dateTo` | string | no | last ~12 months | `YYYY-MM-DD` window | | `includeFullText` | boolean | no | false | Adds complete filing, press release, and transcript text | | `metadataOnly` | boolean | no | false | Skip document parsing; metadata and item codes only | | `onlyNew` | boolean | no | false | Emit only records not returned by previous runs (monitoring) | ### Example input Ticker mode, filings and transcripts together: ```json { "tickers": ["AAPL", "NVDA", "MSFT"], "dataType": "both", "filingsLimit": 5, "transcriptsLimit": 1 } ```` Keyword mode, screening every US filer: ```json { "searchKeyword": "guidance withdrawal", "dataType": "filings", "filingsLimit": 25 } ``` ### Sample output Filing record (trimmed): ```json { "recordType": "filing", "ticker": "AAPL", "companyName": "Apple Inc.", "cik": "0000320193", "formType": "8-K", "accessionNumber": "0000320193-26-000011", "filedDate": "2026-04-30", "acceptanceDateTime": "2026-04-30T20:30:41.000Z", "eventDate": "2026-04-30", "itemCodes": ["2.02", "9.01"], "itemNames": ["Results of Operations and Financial Condition", "Financial Statements and Exhibits"], "title": "Apple Inc. 8-K: Results of Operations and Financial Condition (Item 2.02)", "items": [{"itemCode": "2.02", "itemName": "Results of Operations and Financial Condition", "text": "On April 30, 2026, Apple Inc. issued a press release regarding..."}], "pressRelease": {"headline": "Apple reports second quarter results", "outlookText": null, "text": "..."}, "guidanceSentences": [], "sentiment": {"positive": 18.94, "negative": 16.57, "uncertainty": 6.31, "wordCount": 1267, "netScore": 0.067}, "sentimentNet": 0.067, "url": "https://www.sec.gov/Archives/edgar/data/320193/000032019326000011/", "documentUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019326000011/aapl-20260430.htm", "pressReleaseUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019326000011/a8-kex991q2202603282026.htm" } ``` Transcript record (trimmed): ```json { "recordType": "transcript", "ticker": "AAPL", "companyName": "Apple Inc.", "title": "Apple AAPL Q2 2026 Earnings Call Transcript", "eventDate": "2026-04-30", "fiscalQuarter": "Q2 2026", "fiscalYear": 2026, "participants": [{"name": "Timothy D. Cook", "role": "Chief Executive Officer", "roleType": "executive"}], "preparedRemarks": [{"speaker": "Timothy D. Cook", "role": "Chief Executive Officer", "roleType": "executive", "text": "..."}], "qaPairs": [{ "question": {"speaker": "Erik Woodring", "affiliation": "Morgan Stanley", "text": "..."}, "answers": [{"speaker": "Timothy D. Cook", "role": "Chief Executive Officer", "text": "..."}] }], "guidanceSentences": ["We expect June quarter revenue to grow..."], "sentiment": {"positive": 21.4, "negative": 6.2, "uncertainty": 8.9, "wordCount": 11842, "netScore": 0.637}, "sentimentNet": 0.637, "speakerCount": 13, "questionCount": 16 } ``` ### How to get started 1. Open the actor on Apify: [View on Apify Store](https://apify.com/johnvc/earnings-call-transcript-api?fpr=9n7kx3) 2. Enter one or more tickers (or a search keyword) and click Start. 3. Read your records from the run's dataset as JSON, CSV, or Excel. 8-K data comes from SEC EDGAR (https://www.sec.gov/cgi-bin/browse-edgar), the SEC's official filing system. No API key is required. ### Run from the API ```bash curl -X POST "https://api.apify.com/v2/acts/johnvc~earnings-call-transcript-api/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"tickers": ["NVDA"], "dataType": "both", "filingsLimit": 5, "transcriptsLimit": 1}' ``` ### 🔌 Use this API from Claude (MCP) Add this actor as a tool in [Claude Code](https://claude.ai/referral/uIlpa7nPLg) (free trial), [Claude Cowork](https://claude.ai/referral/uIlpa7nPLg) (free trial), or any other MCP client, via the hosted Apify MCP server. Use this actor-specific URL: https://mcp.apify.com/?tools=actors,docs,johnvc/earnings-call-transcript-api Setup walkthrough: https://www.youtube.com/watch?v=jREWahDGhJM Apify MCP integration docs: https://docs.apify.com/platform/integrations/mcp Your AI agent can then answer questions like "What guidance did NVDA give on its last earnings call?" or "Which companies filed 8-Ks mentioning material weakness this month?" with live structured data. ### n8n integration Available as an n8n community node, **[n8n-nodes-earnings-call-transcript-api](https://www.npmjs.com/package/n8n-nodes-earnings-call-transcript-api)**. In n8n: Settings, Community Nodes, install `n8n-nodes-earnings-call-transcript-api`, then use it in any workflow. It ships Filing and Transcript resources, a full-text Search operation, and works as an AI Agent tool. ### FAQ #### Which companies have transcripts? Roughly 1,000 to 1,500 mostly large and mid cap US companies per earnings quarter, with an archive reaching back to about 2007. 8-K filings cover every US public filer without exception. If a transcript is not available for a ticker, the run returns a clear uncharged note instead of failing. #### How fresh is the data? 8-K records are available minutes after EDGAR accepts the filing; the record carries the exact acceptance timestamp. Transcripts typically publish within hours of the call for large caps, and up to a day or two for smaller names. #### What do the 8-K item codes mean? Every 8-K reports numbered items. The most watched: 2.02 results of operations (earnings), 5.02 executive departures and appointments, 1.05 material cybersecurity incidents, 1.03 bankruptcy, 2.01 completed acquisitions, 7.01 Regulation FD disclosures, 8.01 other events. The actor classifies all items from 1.01 through 9.01 and includes human-readable names in every record. #### Is the sentiment score from an LLM? No. Scores come from a deterministic finance-domain dictionary (positive, negative, and uncertainty word counts per 1,000 words, with negation handling). The same document always produces the same score, which matters for research reproducibility. #### Why did I get fewer results than my limit? The limits are maximums. A company may have fewer 8-Ks in the date window, or fewer transcripts than requested. In keyword mode, only filings matching your phrase count toward the limit. #### Can I search filings without a ticker? Yes. Set `searchKeyword` and leave `tickers` empty to run a full-text search across all US filers. Add `tickers` to narrow the search to specific companies. #### Can I monitor filings on a schedule? Yes. Enable `onlyNew` and add a schedule in Apify. Each run then emits only records that previous runs have not returned, which is ideal for alerting pipelines. Combine with `metadataOnly` for the cheapest possible polling. Last Updated: 2026.07.08 # Actor input Schema ## `tickers` (type: `array`): List stock ticker symbols to fetch, for example 'AAPL' or 'NVDA'. CIK numbers also work. Each ticker is processed independently and tagged in the output. Leave empty only when Search Keyword is set, which switches the Actor to full-text search across all US companies. ## `dataType` (type: `string`): Choose what to return: parsed SEC 8-K filings, structured earnings call transcripts, or both. ## `filingsLimit` (type: `integer`): Set how many 8-K filings to return per ticker, newest first. In keyword search mode this caps total results across all companies. Default 10. ## `transcriptsLimit` (type: `integer`): Set how many earnings call transcripts to return per ticker, newest quarter first. Default 4, which covers one year of calls. ## `searchKeyword` (type: `string`): Search this word or phrase across 8-K filings from ALL US companies using SEC EDGAR full-text search, for example 'guidance withdrawal' or 'material weakness'. When set, tickers become an optional company filter and dataType is treated as 'filings'. ## `eventCategories` (type: `array`): Filter 8-K filings to these event categories, for example 'earnings' or 'executive\_changes'. Each category maps to the matching 8-K item codes. Combine freely with Item Codes below. ## `itemCodes` (type: `array`): Filter 8-K filings to these item codes, for example '2.02' (results of operations), '5.02' (officer departures), or '1.05' (material cybersecurity incidents). Accepts any code from the full 8-K item map 1.01 through 9.01. Leave empty to return filings for all items. ## `dateFrom` (type: `string`): Return only filings and transcripts dated on or after this date, format YYYY-MM-DD, for example 2025-01-01. Leave empty to default to roughly the last 12 months. ## `dateTo` (type: `string`): Return only filings and transcripts dated on or before this date, format YYYY-MM-DD. Leave empty for no upper bound. ## `includeFullText` (type: `boolean`): Include the complete per-item filing text, full press release body, and full transcript in every record. Off by default to keep records small; structured fields (speakers, Q\&A pairs, guidance sentences, sentiment scores) are always included. ## `metadataOnly` (type: `boolean`): Return filing metadata and item codes without fetching or parsing document bodies. Faster and lighter, ideal for alerting on new filings. Off by default. ## `onlyNew` (type: `boolean`): Skip records already returned by previous runs of this Actor on your account. Turn on together with a schedule to emit only newly filed 8-Ks and newly published transcripts on each run. ## Actor input object example ```json { "tickers": [ "AAPL" ], "dataType": "both", "filingsLimit": 10, "transcriptsLimit": 4, "includeFullText": false, "metadataOnly": false, "onlyNew": false } ``` # Actor output Schema ## `records` (type: `string`): Every transcript and filing record stored in the default dataset, with full nested structure (qaPairs, preparedRemarks, participants, items). ## `overview` (type: `string`): Cross-type table: type, ticker, company, date, 8-K items, quarter, sentiment, guidance, and filing link. ## `filings` (type: `string`): SEC 8-K event view: item codes and names, form type, filed/report/acceptance dates, sentiment, and the three EDGAR links. ## `transcripts` (type: `string`): Earnings-call index: fiscal period, call date, speaker/question/word counts, sentiment, and guidance. ## `qaPairs` (type: `string`): One row per analyst Q\&A exchange: question speaker, affiliation, question text, and management answers. Built for RAG and LLM ingestion. ## `participants` (type: `string`): One row per speaker: ticker, company, quarter, name, role, and role type. ## `search` (type: `string`): Full-text keyword-search results: matched keyword, highlighted snippets, matched document, item codes, and EDGAR links. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "tickers": [ "AAPL" ], "dataType": "both" }; // Run the Actor and wait for it to finish const run = await client.actor("johnvc/earnings-call-transcript-api").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "tickers": ["AAPL"], "dataType": "both", } # Run the Actor and wait for it to finish run = client.actor("johnvc/earnings-call-transcript-api").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "tickers": [ "AAPL" ], "dataType": "both" }' | apify call johnvc/earnings-call-transcript-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=johnvc/earnings-call-transcript-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Earnings Call Transcript API - SEC 8-K Filings Parser & Monitor", "description": "Speaker-tagged earnings call transcripts with Q&A pairs, plus SEC 8-K filings parsed from EDGAR: item codes, press releases, guidance sentences, sentiment. Full-text keyword search across all US filers. Pay-per-result, no start fee.", "version": "0.1", "x-build-id": "0VSMHCZPBS0UOKQtW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/johnvc~earnings-call-transcript-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-johnvc-earnings-call-transcript-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/johnvc~earnings-call-transcript-api/runs": { "post": { "operationId": "runs-sync-johnvc-earnings-call-transcript-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/johnvc~earnings-call-transcript-api/run-sync": { "post": { "operationId": "run-sync-johnvc-earnings-call-transcript-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "dataType" ], "properties": { "tickers": { "title": "Tickers", "type": "array", "description": "List stock ticker symbols to fetch, for example 'AAPL' or 'NVDA'. CIK numbers also work. Each ticker is processed independently and tagged in the output. Leave empty only when Search Keyword is set, which switches the Actor to full-text search across all US companies.", "items": { "type": "string" } }, "dataType": { "title": "Data Type", "enum": [ "filings", "transcripts", "both" ], "type": "string", "description": "Choose what to return: parsed SEC 8-K filings, structured earnings call transcripts, or both.", "default": "both" }, "filingsLimit": { "title": "Max Filings Per Ticker", "minimum": 1, "maximum": 200, "type": "integer", "description": "Set how many 8-K filings to return per ticker, newest first. In keyword search mode this caps total results across all companies. Default 10.", "default": 10 }, "transcriptsLimit": { "title": "Max Transcripts Per Ticker", "minimum": 1, "maximum": 40, "type": "integer", "description": "Set how many earnings call transcripts to return per ticker, newest quarter first. Default 4, which covers one year of calls.", "default": 4 }, "searchKeyword": { "title": "Search Keyword (full-text mode)", "type": "string", "description": "Search this word or phrase across 8-K filings from ALL US companies using SEC EDGAR full-text search, for example 'guidance withdrawal' or 'material weakness'. When set, tickers become an optional company filter and dataType is treated as 'filings'." }, "eventCategories": { "title": "Event Categories", "type": "array", "description": "Filter 8-K filings to these event categories, for example 'earnings' or 'executive_changes'. Each category maps to the matching 8-K item codes. Combine freely with Item Codes below.", "items": { "type": "string", "enum": [ "earnings", "guidance", "mergers_acquisitions", "executive_changes", "cybersecurity", "bankruptcy", "restructuring", "accounting_issues", "delisting", "governance", "other_events" ], "enumTitles": [ "Earnings releases (Item 2.02)", "Guidance and Reg FD (Items 2.02, 7.01)", "Mergers and acquisitions (Items 1.01, 1.02, 2.01)", "Executive changes (Item 5.02)", "Cybersecurity incidents (Item 1.05)", "Bankruptcy (Item 1.03)", "Restructuring and impairments (Items 2.05, 2.06)", "Accounting issues (Items 4.01, 4.02)", "Delisting notices (Item 3.01)", "Governance and votes (Items 5.01, 5.03, 5.07)", "Other events (Item 8.01)" ] } }, "itemCodes": { "title": "8-K Item Codes", "type": "array", "description": "Filter 8-K filings to these item codes, for example '2.02' (results of operations), '5.02' (officer departures), or '1.05' (material cybersecurity incidents). Accepts any code from the full 8-K item map 1.01 through 9.01. Leave empty to return filings for all items.", "items": { "type": "string" } }, "dateFrom": { "title": "Date From (YYYY-MM-DD)", "pattern": "^[0-9]{4}-[0-9]{2}-[0-9]{2}$", "type": "string", "description": "Return only filings and transcripts dated on or after this date, format YYYY-MM-DD, for example 2025-01-01. Leave empty to default to roughly the last 12 months." }, "dateTo": { "title": "Date To (YYYY-MM-DD)", "pattern": "^[0-9]{4}-[0-9]{2}-[0-9]{2}$", "type": "string", "description": "Return only filings and transcripts dated on or before this date, format YYYY-MM-DD. Leave empty for no upper bound." }, "includeFullText": { "title": "Include Full Text", "type": "boolean", "description": "Include the complete per-item filing text, full press release body, and full transcript in every record. Off by default to keep records small; structured fields (speakers, Q&A pairs, guidance sentences, sentiment scores) are always included.", "default": false }, "metadataOnly": { "title": "Metadata Only (cheap mode)", "type": "boolean", "description": "Return filing metadata and item codes without fetching or parsing document bodies. Faster and lighter, ideal for alerting on new filings. Off by default.", "default": false }, "onlyNew": { "title": "Only New Records (monitoring)", "type": "boolean", "description": "Skip records already returned by previous runs of this Actor on your account. Turn on together with a schedule to emit only newly filed 8-Ks and newly published transcripts on each run.", "default": false } } }, "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 } } } } } } } } } } ```