# SEC EDGAR Full-Text Search Scraper (`logiover/sec-edgar-fulltext-scraper`) Actor Search all SEC filings (10-K, 8-K, S-1, etc.) by any keyword or phrase via EDGAR full-text search. Extract company name, ticker, CIK, form type, filing date, accession number, and file URL. No API key required. - **URL**: https://apify.com/logiover/sec-edgar-fulltext-scraper.md - **Developed by:** [Logiover](https://apify.com/logiover) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## SEC EDGAR Full-Text Search Scraper — Search All SEC Filings by Keyword, Form Type & Date Search across every public SEC filing ever submitted and extract structured company data, filing metadata, and document links — no API key, no login, no limits. ### What does SEC EDGAR Full-Text Search Scraper do? This actor queries the SEC EDGAR full-text search engine (`efts.sec.gov`) — the same engine powering the official [EDGAR EFTS search interface](https://efts.sec.gov/LATEST/search-index) — to find filings that contain any keyword, phrase, or concept you specify. It supports every form type in the EDGAR database: 10-K annual reports, 8-K material events, S-1 IPO prospectuses, 10-Q quarterly reports, DEF 14A proxy statements, 20-F foreign private issuer filings, and hundreds more. The actor paginates through results using the `from` parameter (100 hits per page), collecting up to your `maxResults` cap. For each matching filing, it parses the Elasticsearch-style hit from the EFTS API and constructs structured output including direct document links, EDGAR filing index URLs, company identifiers, and business metadata. The SEC server is a U.S. government resource with no bot protection — datacenter proxies work reliably, and the official policy merely requires a descriptive `User-Agent` header, which this actor supplies automatically. ### Who is it for? - **Financial analysts and hedge funds** tracking narrative shifts (AI risk, ESG disclosures, supply chain) across thousands of annual reports simultaneously. - **Compliance and legal teams** that need to monitor how specific regulatory language appears in filings across sectors. - **Journalists and investigative reporters** searching for companies mentioning specific topics, events, or counterparties. - **Academic researchers** building datasets of SEC disclosures for NLP, topic modeling, or event studies. - **Corporate intelligence professionals** doing competitive benchmarking by searching for competitor names or product mentions inside rival filings. ### Use cases - Find every 10-K that mentions "artificial intelligence risk" and build a dataset of AI-related risk disclosures across all public companies. - Search for all 8-K filings mentioning a specific executive's name or a named acquisition target to reconstruct M&A timelines. - Track which companies filed S-1 prospectuses disclosing "cryptocurrency" holdings or revenue in a given year. - Pull all DEF 14A proxy statements referencing a specific activist investor or shareholder proposal language. - Monitor real-time filings for new disclosures about a specific geopolitical event, product recall, or regulatory investigation. ### Why use SEC EDGAR Full-Text Search Scraper? - **No API key required** — queries the public EFTS endpoint used by EDGAR's own search UI, free forever. - **14 output fields per filing** — company name, ticker, CIK, form type, filing date, period ending, accession number, document URL, EDGAR index page, description, locations, incorporation states, SIC codes, and relevance score. - **Bulk pagination** — fetches up to 10,000 results per run by paginating 100 hits at a time. - **Flexible form filtering** — filter by one or multiple form types (10-K, 8-K, S-1, etc.) or search across all forms. - **Date range support** — narrow results to a specific date window with `dateFrom` and `dateTo`. - **Export to CSV, JSON, Excel** — all results available via Apify's standard dataset export in any format. ### What data can you extract? The actor returns one row per matching filing document with the following fields: | Field | Type | Description | |-------|------|-------------| | `companyName` | string | Full registered company name (e.g. "Apple Inc.") | | `ticker` | string | Stock ticker symbol(s) (e.g. "AAPL", or "LAAI, VEST" for multiple) | | `cik` | string | SEC Central Index Key — unique company identifier | | `formType` | string | SEC form type (10-K, 8-K, 10-K/A, S-1, etc.) | | `filingDate` | string | Date the filing was submitted (YYYY-MM-DD) | | `periodEnding` | string | Period the filing covers (YYYY-MM-DD), e.g. fiscal year end | | `accessionNo` | string | Accession number (e.g. "0001477932-26-002727") — unique filing ID | | `fileUrl` | string | Direct URL to the primary filing document (HTML/HTM) | | `edgarUrl` | string | EDGAR filing index page URL for the full filing package | | `fileDescription` | string | Human-readable description of the document (e.g. "FORM 10-K ANNUAL REPORT") | | `bizLocations` | string | Business/mailing address(es) from the filing header | | `incStates` | string | State(s) of incorporation | | `sics` | string | SIC industry code(s) for the company | | `relevanceScore` | string | Elasticsearch relevance score (higher = closer match to query) | **Example output record:** ```json { "companyName": "Apple Inc.", "ticker": "AAPL", "cik": "0000320193", "formType": "10-K", "filingDate": "2024-11-01", "periodEnding": "2024-09-28", "accessionNo": "0000320193-24-000123", "fileUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019324000123/aapl-20240928.htm", "edgarUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019324000123/000032019324000123-index.htm", "fileDescription": "FORM 10-K", "bizLocations": "Cupertino, CA", "incStates": "CA", "sics": "3571", "relevanceScore": "18.5" } ```` ### How to use #### Option A — Search by keyword across all forms 1. Set `query` to your search phrase (e.g. `"supply chain disruption"`). 2. Leave `forms` empty (or remove it) to search all form types. 3. Optionally set `dateFrom` and `dateTo` for a date window. 4. Set `maxResults` to how many results you need. **Input JSON:** ```json { "query": "supply chain disruption", "maxResults": 500 } ``` #### Option B — Target specific form types and date range 1. Set `query` to your keyword. 2. Set `forms` to the form types you want (e.g. `["10-K", "10-K/A"]`). 3. Set `dateFrom` and `dateTo` for the filing date window. **Input JSON:** ```json { "query": "cryptocurrency exposure", "forms": ["10-K", "8-K", "S-1"], "dateFrom": "2023-01-01", "dateTo": "2024-12-31", "maxResults": 1000 } ``` ### Input parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `query` | string | *required* | Full-text search keyword or phrase | | `forms` | array | `["10-K"]` | SEC form types to filter by. Empty = all forms | | `dateFrom` | string | `""` | Filing date start filter (YYYY-MM-DD) | | `dateTo` | string | `""` | Filing date end filter (YYYY-MM-DD) | | `maxResults` | integer | `200` | Maximum results to return (1–10000) | | `proxyConfiguration` | object | datacenter | Apify proxy settings | **Full input JSON:** ```json { "query": "artificial intelligence risk", "forms": ["10-K"], "dateFrom": "2022-01-01", "dateTo": "2024-12-31", "maxResults": 200, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [] } } ``` ### Output example ```json { "companyName": "Microsoft Corporation", "ticker": "MSFT", "cik": "0000789019", "formType": "10-K", "filingDate": "2024-07-30", "periodEnding": "2024-06-30", "accessionNo": "0000950170-24-087843", "fileUrl": "https://www.sec.gov/Archives/edgar/data/789019/000095017024087843/msft-20240630.htm", "edgarUrl": "https://www.sec.gov/Archives/edgar/data/789019/000095017024087843/000095017024087843-index.htm", "fileDescription": "FORM 10-K", "bizLocations": "Redmond, WA", "incStates": "WA", "sics": "7372", "relevanceScore": "22.4" } ``` ### Tips for best results - **Use quoted phrases** for exact matches (e.g. `"deepfake risk"`) to find filings that use that precise language. - **Combine with date filters** to track how disclosure language evolved over time — compare 2021 vs. 2024 for the same query. - **Filter by 8-K** for real-time event disclosures — 8-K filings are submitted within 4 business days of a material event. - **Use 10-K for annual risk factor analysis** — annual reports contain the most detailed risk disclosures in Item 1A. - **CIK is your stable ID** — use it to look up all filings by a company at `https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK={cik}`. - **Start broad, then narrow** — run with all forms and a wide date range first to understand result volume, then add filters. - **Cross-reference the accessionNo** — it uniquely identifies the filing; use it to fetch exhibit lists or the full filing index. - **High relevance score = closer keyword match** — sort by `relevanceScore` descending for the most on-topic results. - **For foreign companies**, filter by form type `20-F` (annual) or `6-K` (periodic reports for foreign private issuers). - **Set maxResults to 1000+** for comprehensive market-wide studies; the EDGAR index covers filings back to 1993. ### Integrations Connect SEC EDGAR Full-Text Search Scraper to your existing workflow: - **Google Sheets** — export dataset to Sheets via Apify's native Google Sheets integration; auto-refresh on a schedule. - **Slack** — configure webhooks to notify your team when new filings matching your query appear. - **Zapier / Make** — connect to 1000s of apps; trigger workflows when new filing data is available. - **Webhooks** — set up Apify webhooks to POST results to your own API endpoint on run completion. - **Schedule** — run weekly or daily to monitor new filings for your query terms as companies file. ### API usage **cURL:** ```bash curl -X POST \ "https://api.apify.com/v2/acts/logiover~sec-edgar-fulltext-scraper/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "query": "artificial intelligence risk", "forms": ["10-K"], "maxResults": 200 }' ``` **Node.js (Apify client):** ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_TOKEN' }); const run = await client.actor('logiover/sec-edgar-fulltext-scraper').call({ query: 'artificial intelligence risk', forms: ['10-K'], maxResults: 200, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` **Python:** ```python from apify_client import ApifyClient client = ApifyClient("YOUR_TOKEN") run = client.actor("logiover/sec-edgar-fulltext-scraper").call(run_input={ "query": "artificial intelligence risk", "forms": ["10-K"], "maxResults": 200, }) items = client.dataset(run["defaultDatasetId"]).list_items().items print(items) ``` ### Use with AI agents (MCP) SEC EDGAR Full-Text Search Scraper is compatible with the [Apify MCP server](https://apify.com/apify/actors-mcp-server), allowing AI agents like Claude, GPT-4, and others to search SEC filings directly via tool calls. Connect the MCP server and your agent can answer questions like: *"Find all 10-K filings from 2023 mentioning 'PFAS exposure' and list the companies by relevance score"* — without any manual data extraction. ### FAQ #### Does this actor require an API key or login? No. The SEC EDGAR full-text search endpoint (`efts.sec.gov`) is fully public and requires no authentication. The only requirement is a descriptive `User-Agent` header, which is set automatically. #### How far back does the coverage go? The EDGAR database contains filings from 1993 onwards. Full-text search coverage depends on whether the document was submitted in text/HTML format — most filings from 1996 onward are fully indexed. Very old scanned PDFs may not be searchable. #### How many results can I get per run? The theoretical maximum is 10,000 results per run (EDGAR's ES index caps at 10,000 for any query). Set `maxResults` up to 10000. Each page fetches 100 results; a 10,000-result run makes 100 API calls. #### Why do I get 0 results? Check your query spelling and try broader terms. Very narrow phrases may have no exact matches. Also verify the form type filter — e.g. `10-K/A` is distinct from `10-K`. Try removing form and date filters first. #### Why are some fields null? Not all filings have every metadata field populated. Foreign issuers often lack US state fields. Companies without a ticker (e.g. reporting-only entities) will have `ticker: null`. #### Can I export results to CSV or Excel? Yes. After the run, go to the dataset and click "Export" — choose CSV, JSON, Excel, or XML. You can also use the Apify API to fetch the dataset programmatically. #### How fast is a run? A 200-result run typically completes in under 30 seconds. A 10,000-result run takes about 5 minutes. The SEC EDGAR API is fast and rate-limiting is minimal for well-behaved clients. #### Is there a rate limit on the SEC EDGAR server? The SEC recommends no more than 10 requests per second and requires a descriptive User-Agent. This actor throttles automatically and will not hit rate limits under normal use. #### Is it legal to scrape EDGAR? Yes. SEC EDGAR is a U.S. government public database maintained for investor access. All data is in the public domain. The SEC's [access policies](https://www.sec.gov/privacy.htm#edgarwebsites) permit automated access with a proper User-Agent header. #### How often is EDGAR updated? The SEC processes filings continuously on business days. New 8-K filings appear within hours of submission. Schedule this actor daily to capture new filings as they appear. #### Can I search for multiple keywords at once? Yes — EDGAR's full-text search supports boolean operators. Try `"supply chain" AND "force majeure"` or `"cybersecurity" OR "data breach"` in your query field. #### What form types are available? All SEC forms are searchable: 10-K, 10-Q, 8-K, S-1, S-11, 20-F, 6-K, DEF 14A, SC 13G, Form 4, Form 13F, and 100+ more. Leave `forms` empty to search all. ### Is it legal? This actor accesses the [SEC EDGAR Full-Text Search System](https://efts.sec.gov/LATEST/search-index), a public U.S. government service provided by the Securities and Exchange Commission. All data returned is in the public domain and freely accessible per U.S. government open data policy. No login, scraping of private content, or circumvention of access controls is involved. Users are responsible for ensuring their use of financial disclosure data complies with applicable securities laws and their organization's policies. ### Related scrapers - [logiover/b2b-lead-scraper](https://apify.com/logiover/b2b-lead-scraper) — Extract B2B leads by sector and country from OpenStreetMap. - [logiover/comtrade-trade-data-scraper](https://apify.com/logiover/comtrade-trade-data-scraper) — UN Comtrade international trade flow data. - [logiover/company-dossier-generator](https://apify.com/logiover/company-dossier-generator) — AI-generated company intelligence dossiers from public sources. - [logiover/github-activity-monitor](https://apify.com/logiover/github-activity-monitor) — Monitor GitHub repos for commits, issues, and releases. # Actor input Schema ## `query` (type: `string`): Full-text keyword or phrase to search across all SEC filings (e.g. 'artificial intelligence risk', 'cryptocurrency exposure', 'supply chain disruption'). Leave empty to run the default broad search and pull recent filings. ## `forms` (type: `array`): Filter by one or more SEC form types. Leave empty to search all forms. ## `sort` (type: `string`): Order of returned rows. 'Relevance' uses EDGAR's full-text ranking. 'Newest first' / 'Oldest first' re-sort the collected results by filing date. ## `dateFrom` (type: `string`): Start date filter in YYYY-MM-DD format (e.g. 2023-01-01). Leave empty for no start date filter. ## `dateTo` (type: `string`): End date filter in YYYY-MM-DD format (e.g. 2024-12-31). Leave empty for no end date filter. ## `maxResults` (type: `integer`): Maximum number of filing results to return. Default 200, max 10000. ## `proxyConfiguration` (type: `object`): Apify proxy settings. Defaults to Apify Proxy (AUTO). SEC EDGAR is an open government server, so a direct connection is used automatically as a fallback if the proxy fails. ## Actor input object example ```json { "query": "artificial intelligence", "forms": [], "sort": "relevance", "dateFrom": "", "dateTo": "", "maxResults": 200, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): All records extracted by this run. Open the Dataset tab to browse, filter, and export as CSV, JSON, or Excel. # 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 = { "query": "artificial intelligence", "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("logiover/sec-edgar-fulltext-scraper").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 = { "query": "artificial intelligence", "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("logiover/sec-edgar-fulltext-scraper").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 '{ "query": "artificial intelligence", "proxyConfiguration": { "useApifyProxy": true } }' | apify call logiover/sec-edgar-fulltext-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=logiover/sec-edgar-fulltext-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR Full-Text Search Scraper", "description": "Search all SEC filings (10-K, 8-K, S-1, etc.) by any keyword or phrase via EDGAR full-text search. Extract company name, ticker, CIK, form type, filing date, accession number, and file URL. No API key required.", "version": "1.0", "x-build-id": "mEt1nPcqqRi0ajtec" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/logiover~sec-edgar-fulltext-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-logiover-sec-edgar-fulltext-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/logiover~sec-edgar-fulltext-scraper/runs": { "post": { "operationId": "runs-sync-logiover-sec-edgar-fulltext-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/logiover~sec-edgar-fulltext-scraper/run-sync": { "post": { "operationId": "run-sync-logiover-sec-edgar-fulltext-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "query": { "title": "Search Query", "type": "string", "description": "Full-text keyword or phrase to search across all SEC filings (e.g. 'artificial intelligence risk', 'cryptocurrency exposure', 'supply chain disruption'). Leave empty to run the default broad search and pull recent filings." }, "forms": { "title": "Form Types (optional)", "uniqueItems": true, "type": "array", "description": "Filter by one or more SEC form types. Leave empty to search all forms.", "items": { "type": "string", "enum": [ "10-K", "10-Q", "8-K", "S-1", "S-3", "S-4", "424B5", "20-F", "40-F", "6-K", "DEF 14A", "DEFA14A", "DEFM14A", "PRE 14A", "13F-HR", "SC 13D", "SC 13G", "SC 14D9", "SC TO-T", "4", "3", "5", "11-K", "10-K/A", "10-Q/A", "8-K/A", "N-1A", "N-CSR", "N-Q", "497", "F-1", "F-3", "F-4", "425", "POS AM", "CORRESP", "UPLOAD" ], "enumTitles": [ "10-K (annual report)", "10-Q (quarterly report)", "8-K (current report)", "S-1 (IPO registration)", "S-3 (shelf registration)", "S-4 (M&A registration)", "424B5 (prospectus)", "20-F (foreign annual report)", "40-F (Canadian annual)", "6-K (foreign current report)", "DEF 14A (proxy statement)", "DEFA14A (additional proxy)", "DEFM14A (merger proxy)", "PRE 14A (preliminary proxy)", "13F-HR (institutional holdings)", "SC 13D (>5% activist stake)", "SC 13G (>5% passive stake)", "SC 14D9 (tender recommendation)", "SC TO-T (tender offer)", "Form 4 (insider transaction)", "Form 3 (initial insider)", "Form 5 (annual insider)", "11-K (employee benefit plan)", "10-K/A (amended annual)", "10-Q/A (amended quarterly)", "8-K/A (amended current)", "N-1A (fund registration)", "N-CSR (fund shareholder report)", "N-Q (fund holdings)", "497 (fund prospectus)", "F-1 (foreign IPO)", "F-3 (foreign shelf)", "F-4 (foreign M&A)", "425 (merger comms)", "POS AM (post-effective amendment)", "CORRESP (SEC correspondence)", "UPLOAD (SEC comment letter)" ] }, "default": [] }, "sort": { "title": "Sort Order", "enum": [ "relevance", "dateDesc", "dateAsc" ], "type": "string", "description": "Order of returned rows. 'Relevance' uses EDGAR's full-text ranking. 'Newest first' / 'Oldest first' re-sort the collected results by filing date.", "default": "relevance" }, "dateFrom": { "title": "Date From (optional)", "type": "string", "description": "Start date filter in YYYY-MM-DD format (e.g. 2023-01-01). Leave empty for no start date filter.", "default": "" }, "dateTo": { "title": "Date To (optional)", "type": "string", "description": "End date filter in YYYY-MM-DD format (e.g. 2024-12-31). Leave empty for no end date filter.", "default": "" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of filing results to return. Default 200, max 10000.", "default": 200 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Apify proxy settings. Defaults to Apify Proxy (AUTO). SEC EDGAR is an open government server, so a direct connection is used automatically as a fallback if the proxy fails.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```