# SEC EDGAR Scraper (`constructive_calm/sec-edgar-scraper`) Actor Fetches SEC EDGAR filings, normalized financial statements, XBRL facts, insider trades (Form 4), institutional holdings (13F), activist stakes (13D/G), full-text search hits, and parsed 8-K items via official SEC APIs. Zero anti-bot. Optional AI summaries. - **URL**: https://apify.com/constructive\_calm/sec-edgar-scraper.md - **Developed by:** [Omar Eldeeb](https://apify.com/constructive_calm) (community) - **Categories:** News, Developer tools, SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.40 / 1,000 filing fetcheds 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 ### What does SEC EDGAR Scraper do? SEC EDGAR Scraper fetches structured data directly from the U.S. Securities and Exchange Commission's official [EDGAR](https://www.sec.gov/edgar) system — every public filing, every XBRL financial fact, every insider trade, every institutional holding — and delivers it as clean JSON or CSV you can feed straight into a pipeline. It uses the SEC's official data APIs (`data.sec.gov`, `efts.sec.gov`, `www.sec.gov/Archives/edgar`), which are public-domain, zero-auth, and fully commercial-safe. No CAPTCHAs, no scraping fragility — just the same data that Bloomberg, FactSet, and sec-api.io resell, delivered cheaper and on your own Apify schedule. Built with TypeScript on the Apify SDK. Respects SEC fair-use limits automatically, so it never gets throttled. ### Why use SEC EDGAR Scraper? - **Financial analysts** — pull normalized income statements, balance sheets, and cash flows for any U.S. public company with one call. No more wrestling with XBRL. - **Hedge funds & quants** — monitor insider trades (Form 4), institutional position changes (13F), and activist stake accumulations (13D/G) as filings land. - **M&A / PE dealmakers** — auto-parse 8-K item codes (2.01 acquisitions, 5.02 exec changes, 4.01 auditor changes) to surface deal signals the moment they're filed. - **Investment research & AI/LLM teams** — pipe 20+ years of filings into your model with structured metadata, AI-generated filing summaries, and full-text search. - **Compliance & governance teams** — track peer filings, proxy statements, and disclosure trends with date-range filters and scheduled runs. ### How to use SEC EDGAR Scraper 1. Pick a **mode**: `filings`, `xbrl_facts`, `financials`, `full_text_search`, `form4`, `form13f`, `activist`, `latest_feed`, or `eight_k_items`. 2. For company-scoped modes, add one or more **tickers** (e.g. `AAPL`, `TSLA`) — or CIKs, company names, or domains. The actor auto-resolves to canonical SEC CIK. 3. Optional filters: `forms` (10-K, 10-Q, 8-K, etc.), `dateFrom` / `dateTo`, `maxItems`, form-specific filters. 4. Run the actor. Results land in the default dataset. 5. Export as **JSON, CSV, Excel, or XML** from the Apify Console — or pipe into a webhook / pull via API. 6. Want daily updates? Enable **incremental mode** and schedule the actor to run daily — only new or changed items are emitted. ### Input The simplest possible input — fetch Apple's recent 10-K and 10-Q filings: ```json { "mode": "filings", "tickers": ["AAPL"], "forms": ["10-K", "10-Q"], "maxItems": 20 } ```` Get normalized income statements for Microsoft over the past 5 fiscal years: ```json { "mode": "financials", "tickers": ["MSFT"], "statementTypes": ["income_statement"], "fiscalPeriods": ["FY"], "dateFrom": "2020-01-01", "maxItems": 10 } ``` Find every 10-K that mentions "artificial intelligence" in 2025: ```json { "mode": "full_text_search", "searchQuery": "artificial intelligence", "forms": ["10-K"], "dateFrom": "2025-01-01", "dateTo": "2025-12-31", "maxItems": 500 } ``` Track recent insider buying at Tesla worth at least $100,000: ```json { "mode": "form4", "tickers": ["TSLA"], "transactionCodes": ["P"], "minTransactionValue": 100000, "dateFrom": "2025-01-01", "maxItems": 50 } ``` Pull 13F institutional holdings for Berkshire Hathaway (CIK 1067983): ```json { "mode": "form13f", "tickers": ["1067983"], "maxItems": 500 } ``` Get activist (SC 13D) stake accumulations for any ticker under pressure: ```json { "mode": "activist", "tickers": ["DIS"], "activistOnly": true, "maxItems": 20 } ``` Generate AI-powered summaries of a company's 8-K earnings releases: ```json { "mode": "eight_k_items", "tickers": ["NVDA"], "eightKItemCodes": ["2.02"], "enableAiSummary": true, "maxItems": 8 } ``` ### Output Example output from `filings` mode: ```json { "type": "filing", "cik": "320193", "ticker": "AAPL", "companyName": "Apple Inc.", "form": "10-K", "accessionNumber": "0000320193-25-000079", "filingDate": "2025-10-31", "reportDate": "2025-09-27", "acceptanceDateTime": "2025-10-31T18:04:43.000Z", "primaryDocument": "aapl-20250927.htm", "primaryDocDescription": "10-K", "items": null, "isXBRL": true, "isInlineXBRL": true, "size": 6391250, "filingUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm", "filingIndexUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/0000320193-25-000079-index.htm", "aiSummary": null, "scrapedAt": "2026-04-19T20:05:49.147Z" } ``` Example output from `financials` mode (normalized income statement): ```json { "type": "financial_statement", "cik": "320193", "ticker": "AAPL", "companyName": "Apple Inc.", "statementType": "income_statement", "period": "2025-FY", "periodEnd": "2024-09-28", "fiscalYear": 2025, "fiscalPeriod": "FY", "form": "10-K", "filedDate": "2025-10-31", "accessionNumber": "0000320193-25-000079", "currency": "USD", "lineItems": [ { "label": "Revenue", "concept": "RevenueFromContractWithCustomerExcludingAssessedTax", "value": 383285000000, "unit": "USD" }, { "label": "Cost of Revenue", "concept": "CostOfGoodsAndServicesSold", "value": 214137000000, "unit": "USD" }, { "label": "Gross Profit", "concept": "GrossProfit", "value": 169148000000, "unit": "USD" }, { "label": "Operating Income", "concept": "OperatingIncomeLoss", "value": 114301000000, "unit": "USD" }, { "label": "Net Income", "concept": "NetIncomeLoss", "value": 96995000000, "unit": "USD" }, { "label": "EPS Diluted", "concept": "EarningsPerShareDiluted", "value": 6.13, "unit": "USD/shares" } ] } ``` Example output from `form4` mode (insider trade): ```json { "type": "form4_transaction", "cik": "320193", "ticker": "AAPL", "companyName": "Apple Inc.", "insiderName": "Borders Ben", "insiderCik": "0002100523", "insiderTitle": "Principal Accounting Officer", "isOfficer": true, "isDirector": false, "isTenPercentOwner": false, "transactionType": "other", "transactionCode": "F", "shares": 892, "pricePerShare": 266.43, "totalValue": 237655.56, "sharesOwnedAfter": 39987, "transactionDate": "2026-04-15", "filingDate": "2026-04-17" } ``` #### Data fields | Field | Type | Description | |---|---|---| | `type` | enum | Discriminator: `filing`, `xbrl_fact`, `financial_statement`, `full_text_hit`, `form4_transaction`, `form13f_holding`, `activist_filing`, `eight_k_parsed` | | `cik` | string | SEC Central Index Key (company identifier) | | `ticker` | string? | Stock ticker, when known | | `companyName` | string | Registrant name as filed | | `form` | string | Form type (10-K, 10-Q, 8-K, 4, 13F-HR, SC 13D, etc.) | | `filingDate` | date | When the filing was submitted to SEC | | `reportDate` | date? | Period the filing reports on (e.g. fiscal year-end) | | `accessionNumber` | string | Unique SEC filing identifier | | `filingUrl` | url | Deep link to the primary filing document | | `filingIndexUrl` | url | Deep link to the filing's index page (all exhibits) | | `scrapedAt` | timestamp | When this record was emitted by the actor | | `aiSummary` | object? | AI-generated structured summary (only when `enableAiSummary` is on) | Mode-specific fields (line items, transactions, XBRL facts) are documented inside each mode's output rows — see the examples above. ### How much does it cost to scrape SEC EDGAR? Pay only for what you use. Each chargeable event has its own price: | Event | Price | When it fires | |---|---|---| | `filing-fetched` | **$0.40 per 1,000** | Any filing, insider trade, 8-K item, activist stake, or 13F holding emitted | | `xbrl-fact-fetched` | **$0.15 per 1,000** | Raw XBRL financial fact (one revenue data point, one EPS number, etc.) | | `normalized-statement-fetched` | **$0.50 per 1,000** | A clean, analyst-ready financial statement (income, balance, cash flow) | | `fulltext-hit-fetched` | **$0.30 per 1,000** | A filing matched by your full-text search query | | `change-detected` | **$0.30 per 1,000** | A new or updated item surfaced via incremental mode | | `ai-summary-generated` | **$0.05 each** | An AI structured summary (premium; only when `enableAiSummary` is on) | **Free trial:** The first **50 chargeable events per run are free.** Test any mode, see real output, pay nothing until you're confident. **Typical run costs** (after the free trial): | Task | Events | Cost | |---|---|---| | Fetch 500 recent filings for 5 tickers | 500 filings | **$0.18** | | Pull 10 years of quarterly financials for a single ticker | 120 statements | **$0.04** | | Full-text search "AI" across 2025 10-Ks (top 1000 hits) | 1,000 hits | **$0.29** | | 500 insider trades at 20 S\&P 500 companies | 500 filings | **$0.18** | | Track 13F holdings for 3 hedge funds (8000 holdings) | 8,000 filings | **$3.02** | | AI-summarize 50 earnings 8-Ks | 50 filings + 50 summaries | **$2.52** | Compared to sec-api.io ($100/mo minimum) and Bloomberg terminals ($24k/user/year), this actor pays off even at heavy use. ### Tips & advanced options - **Incremental mode** — set `incrementalMode: true` and schedule the actor (e.g. daily at 09:00 EST). On each run, only new or changed items are emitted, so your downstream systems see a clean delta stream. - **Combining filters** — all company-scoped modes accept `forms` and `dateFrom` / `dateTo` together. Example: recent 10-Q filings from the past 90 days for a watchlist of 50 tickers. - **Custom XBRL concepts** — in `xbrl_facts` mode, provide the exact US-GAAP concept names (e.g. `StockholdersEquity`, `LongTermDebtNoncurrent`). See [SEC's XBRL taxonomy](https://www.sec.gov/dera/data/financial-statement-data-sets) for the full catalog. - **Multi-ticker runs** — the `tickers` field accepts an array. One run for 100 companies is cheaper than 100 runs for 1 company each (fewer actor-start charges). - **AI summaries on long filings** — set `aiSummaryMaxChars` to truncate input. For 10-Ks (often 100k+ chars), 60k is usually enough to catch all material items. - **Chaining with Apify webhooks** — pipe results into Make.com, Zapier, Power BI, or a Slack channel using Apify's integrations. ### Legal disclaimer EDGAR is a U.S. government system operated by the Securities and Exchange Commission. Data returned by this actor is public-domain and subject to the [SEC.gov Privacy and Security Policy](https://www.sec.gov/privacy). This actor operates within SEC's [published fair-use guidelines](https://www.sec.gov/os/accessing-edgar-data) (≤10 requests/second, User-Agent header with contact info). You are responsible for complying with any downstream redistribution terms (e.g. GDPR if you're processing EU-linked data, or your local data-handling laws). ### FAQ & support **Does this actor require an SEC API key?** No. SEC EDGAR APIs are public-domain and unauthenticated. This actor sends a compliant User-Agent header automatically. **How fresh is the data?** Filings appear in the submissions API within seconds of SEC acceptance. XBRL fact APIs can lag by a minute during 8-K peak hours. Full-text search index lags by 15–30 minutes on average. **What if my ticker isn't resolving?** The SEC ticker list covers ~8,000 U.S.-listed public companies. For foreign filers (20-F issuers), closed-end funds, and some OTC stocks, pass the CIK directly in `tickers` (e.g. `"1067983"` for Berkshire Hathaway). **Can I run this on a schedule?** Yes. Set `incrementalMode: true` and use Apify's scheduler. Daily runs after 6pm ET (after daily SEC close) catch the full day's filings. **What about 10-K amendments and restatements?** Amendments (`10-K/A`, `10-Q/A`) are returned as separate filings with the amendment form code. Use `forms: ["10-K", "10-K/A"]` to get both originals and amendments. **Something's wrong / I have a feature request.** Open an issue on the actor's Issues tab or email the maintainer. Common requests (peer benchmarking, risk-factor diffing, proxy statement parsing) are on the roadmap. # Actor input Schema ## `mode` (type: `string`): What to fetch. 'filings' returns all filings for a company. 'xbrl\_facts' returns raw XBRL data points (e.g. revenue history). 'financials' returns normalized income statements / balance sheets / cash flows. 'full\_text\_search' searches the EDGAR full-text index. 'form4' returns insider trades. 'form13f' returns institutional fund holdings. 'activist' returns 13D/G activist positions. 'latest\_feed' returns the newest filings across all companies (filterable by form type). 'eight\_k\_items' parses 8-K item codes (acquisitions, exec changes, auditor changes, etc.). ## `tickers` (type: `array`): One or more tickers (AAPL), company names (Apple Inc), domains (apple.com), or CIKs (0000320193). The actor auto-resolves to canonical CIK. Used by all company-scoped modes. ## `forms` (type: `array`): Filter filings by form type. Leave empty for all forms. Examples: 10-K (annual), 10-Q (quarterly), 8-K (current report), S-1 (IPO), 20-F (foreign), DEF 14A (proxy), 4 (insider), 13F-HR (institutional holdings), SC 13D / SC 13G (activist positions), 10-K/A (amendment). ## `maxItems` (type: `integer`): Maximum number of items to return. Varies by mode: in filings mode this is total filings across all tickers; in xbrl\_facts mode this caps the number of fact rows; in full\_text\_search mode this caps the number of hits. ## `dateFrom` (type: `string`): Only return filings filed on or after this date (YYYY-MM-DD). Leave empty for no lower bound. ## `dateTo` (type: `string`): Only return filings filed on or before this date (YYYY-MM-DD). Leave empty for no upper bound. ## `xbrlConcepts` (type: `array`): US-GAAP or DEI XBRL concept names to fetch in 'xbrl\_facts' mode. Common examples: Revenues, NetIncomeLoss, CashAndCashEquivalentsAtCarryingValue, Assets, Liabilities, StockholdersEquity, EarningsPerShareBasic. Leave empty to fetch all available concepts for the company (high volume). ## `statementTypes` (type: `array`): Which normalized statements to generate in 'financials' mode. ## `fiscalPeriods` (type: `array`): Filter normalized statements by fiscal period. FY = full fiscal year (from 10-K), Q1/Q2/Q3/Q4 = quarters (from 10-Q). Leave empty for all. ## `searchQuery` (type: `string`): Keyword or phrase to search in EDGAR full-text index. Required when mode is 'full\_text\_search'. Supports quotes for exact phrases, e.g. "artificial intelligence". Supports operators: AND, OR, NOT. Example: "climate risk" AND "supply chain". ## `searchCiks` (type: `array`): Restrict full-text search to specific company CIKs. Leave empty to search all companies. ## `transactionCodes` (type: `array`): Filter Form 4 insider trades by transaction code. P = open-market purchase, S = open-market sale, A = grant/award, M = option exercise, F = tax withhold, G = gift, D = disposition to issuer. Leave empty for all codes. ## `minTransactionValue` (type: `integer`): Skip Form 4 insider transactions with a total value below this amount. 0 = no filter. Useful for filtering out noise. ## `activistOnly` (type: `boolean`): If enabled, activist mode returns only SC 13D filings (active campaigns) and excludes SC 13G (passive 5%+ holdings). Default returns both. ## `eightKItemCodes` (type: `array`): Filter 8-K filings by item code. Common items: 1.01 (material agreement), 2.01 (acquisition completion), 2.02 (earnings release), 4.01 (auditor change), 5.02 (exec departure/appointment), 5.07 (shareholder vote), 7.01 (Reg FD), 8.01 (other material). Leave empty for all. ## `incrementalMode` (type: `boolean`): If enabled, the actor saves a fingerprint of the last run and, on the next run with the same input, only emits items that are new or changed. Ideal for scheduled daily runs. ## `enableAiSummary` (type: `boolean`): If enabled, an AI-powered structured summary is generated for each filing via Gemini 2.5 Flash. Adds $0.05 per summary. Summaries include key financial highlights, material risks, tone analysis, and notable changes. ## `aiSummaryMaxChars` (type: `integer`): Cap the filing text fed to the AI at this many characters (from the start of the filing body). Longer filings are truncated. Lower values = cheaper, faster, but may miss tail content. ## `proxyConfiguration` (type: `object`): The SEC EDGAR API does not require proxies (no anti-bot, only fair-use rate limits). Leave empty in most cases. If you have a specific network policy, configure proxies here. ## Actor input object example ```json { "mode": "filings", "tickers": [ "AAPL" ], "forms": [ "10-K", "10-Q", "8-K" ], "maxItems": 100, "dateFrom": "", "dateTo": "", "xbrlConcepts": [ "Revenues", "NetIncomeLoss", "Assets" ], "statementTypes": [ "income_statement", "balance_sheet", "cash_flow" ], "fiscalPeriods": [], "searchQuery": "artificial intelligence", "searchCiks": [], "transactionCodes": [ "P", "S" ], "minTransactionValue": 0, "activistOnly": false, "eightKItemCodes": [ "2.02", "5.02" ], "incrementalMode": false, "enableAiSummary": false, "aiSummaryMaxChars": 40000, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `dataset` (type: `string`): Dataset of SEC filings, XBRL facts, financial statements, and related items. # 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" ], "forms": [ "10-K", "10-Q", "8-K" ], "maxItems": 100, "xbrlConcepts": [ "Revenues", "NetIncomeLoss", "Assets" ], "searchQuery": "artificial intelligence", "transactionCodes": [ "P", "S" ], "eightKItemCodes": [ "2.02", "5.02" ], "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("constructive_calm/sec-edgar-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 = { "tickers": ["AAPL"], "forms": [ "10-K", "10-Q", "8-K", ], "maxItems": 100, "xbrlConcepts": [ "Revenues", "NetIncomeLoss", "Assets", ], "searchQuery": "artificial intelligence", "transactionCodes": [ "P", "S", ], "eightKItemCodes": [ "2.02", "5.02", ], "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("constructive_calm/sec-edgar-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 '{ "tickers": [ "AAPL" ], "forms": [ "10-K", "10-Q", "8-K" ], "maxItems": 100, "xbrlConcepts": [ "Revenues", "NetIncomeLoss", "Assets" ], "searchQuery": "artificial intelligence", "transactionCodes": [ "P", "S" ], "eightKItemCodes": [ "2.02", "5.02" ], "proxyConfiguration": { "useApifyProxy": false } }' | apify call constructive_calm/sec-edgar-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=constructive_calm/sec-edgar-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR Scraper", "description": "Fetches SEC EDGAR filings, normalized financial statements, XBRL facts, insider trades (Form 4), institutional holdings (13F), activist stakes (13D/G), full-text search hits, and parsed 8-K items via official SEC APIs. Zero anti-bot. Optional AI summaries.", "version": "1.0", "x-build-id": "4LKVCpy95132aYWi3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/constructive_calm~sec-edgar-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-constructive_calm-sec-edgar-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/constructive_calm~sec-edgar-scraper/runs": { "post": { "operationId": "runs-sync-constructive_calm-sec-edgar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/constructive_calm~sec-edgar-scraper/run-sync": { "post": { "operationId": "run-sync-constructive_calm-sec-edgar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "mode" ], "properties": { "mode": { "title": "Scraping mode", "enum": [ "filings", "xbrl_facts", "financials", "full_text_search", "form4", "form13f", "activist", "latest_feed", "eight_k_items" ], "type": "string", "description": "What to fetch. 'filings' returns all filings for a company. 'xbrl_facts' returns raw XBRL data points (e.g. revenue history). 'financials' returns normalized income statements / balance sheets / cash flows. 'full_text_search' searches the EDGAR full-text index. 'form4' returns insider trades. 'form13f' returns institutional fund holdings. 'activist' returns 13D/G activist positions. 'latest_feed' returns the newest filings across all companies (filterable by form type). 'eight_k_items' parses 8-K item codes (acquisitions, exec changes, auditor changes, etc.).", "default": "filings" }, "tickers": { "title": "Tickers or company names", "type": "array", "description": "One or more tickers (AAPL), company names (Apple Inc), domains (apple.com), or CIKs (0000320193). The actor auto-resolves to canonical CIK. Used by all company-scoped modes.", "default": [], "items": { "type": "string" } }, "forms": { "title": "Form types filter", "type": "array", "description": "Filter filings by form type. 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Leave empty for no upper bound.", "default": "" }, "xbrlConcepts": { "title": "XBRL concepts (facts mode)", "type": "array", "description": "US-GAAP or DEI XBRL concept names to fetch in 'xbrl_facts' mode. Common examples: Revenues, NetIncomeLoss, CashAndCashEquivalentsAtCarryingValue, Assets, Liabilities, StockholdersEquity, EarningsPerShareBasic. Leave empty to fetch all available concepts for the company (high volume).", "default": [], "items": { "type": "string" } }, "statementTypes": { "title": "Financial statement types", "type": "array", "description": "Which normalized statements to generate in 'financials' mode.", "items": { "type": "string", "enum": [ "income_statement", "balance_sheet", "cash_flow" ], "enumTitles": [ "Income statement", "Balance sheet", "Cash flow" ] }, "default": [ "income_statement", "balance_sheet", "cash_flow" ] }, "fiscalPeriods": { "title": "Fiscal periods", "type": "array", "description": "Filter normalized statements by fiscal period. FY = full fiscal year (from 10-K), Q1/Q2/Q3/Q4 = quarters (from 10-Q). Leave empty for all.", "items": { "type": "string", "enum": [ "FY", "Q1", "Q2", "Q3", "Q4" ], "enumTitles": [ "Full fiscal year", "Q1", "Q2", "Q3", "Q4" ] }, "default": [] }, "searchQuery": { "title": "Full-text search query", "type": "string", "description": "Keyword or phrase to search in EDGAR full-text index. Required when mode is 'full_text_search'. Supports quotes for exact phrases, e.g. \"artificial intelligence\". Supports operators: AND, OR, NOT. Example: \"climate risk\" AND \"supply chain\".", "default": "" }, "searchCiks": { "title": "Limit search to CIKs", "type": "array", "description": "Restrict full-text search to specific company CIKs. Leave empty to search all companies.", "default": [], "items": { "type": "string" } }, "transactionCodes": { "title": "Transaction codes (Form 4)", "type": "array", "description": "Filter Form 4 insider trades by transaction code. P = open-market purchase, S = open-market sale, A = grant/award, M = option exercise, F = tax withhold, G = gift, D = disposition to issuer. Leave empty for all codes.", "default": [], "items": { "type": "string" } }, "minTransactionValue": { "title": "Min transaction value (USD)", "minimum": 0, "type": "integer", "description": "Skip Form 4 insider transactions with a total value below this amount. 0 = no filter. Useful for filtering out noise.", "default": 0 }, "activistOnly": { "title": "Activist filings only (SC 13D)", "type": "boolean", "description": "If enabled, activist mode returns only SC 13D filings (active campaigns) and excludes SC 13G (passive 5%+ holdings). Default returns both.", "default": false }, "eightKItemCodes": { "title": "8-K item codes", "type": "array", "description": "Filter 8-K filings by item code. Common items: 1.01 (material agreement), 2.01 (acquisition completion), 2.02 (earnings release), 4.01 (auditor change), 5.02 (exec departure/appointment), 5.07 (shareholder vote), 7.01 (Reg FD), 8.01 (other material). Leave empty for all.", "default": [], "items": { "type": "string" } }, "incrementalMode": { "title": "Incremental mode (change detection)", "type": "boolean", "description": "If enabled, the actor saves a fingerprint of the last run and, on the next run with the same input, only emits items that are new or changed. Ideal for scheduled daily runs.", "default": false }, "enableAiSummary": { "title": "Enable AI summary (premium)", "type": "boolean", "description": "If enabled, an AI-powered structured summary is generated for each filing via Gemini 2.5 Flash. Adds $0.05 per summary. 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