# SourceReceipt - Source Verification for AI Agents (`sassy_labs/source-receipt-evidence-gate`) Actor Verify sources and citations before AI agents act. Check public URLs for required, contradictory, or stale evidence and return structured receipts with exact snippets, redirects, dates, and SHA-256 hashes. - **URL**: https://apify.com/sassy\_labs/source-receipt-evidence-gate.md - **Developed by:** [Sassy Labs](https://apify.com/sassy_labs) (community) - **Categories:** AI, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 source receipts 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## SourceReceipt - Source Verification for AI Agents SourceReceipt is a deterministic **source-verification and citation-checking utility for AI agents**. Before an agent acts on a price, deadline, eligibility rule, policy, availability statement, or other time-sensitive claim, it checks the cited public URL against explicit machine-readable evidence requirements. It returns one compact receipt per URL: HTTP status, final URL, page title, declared content date, freshness, normalized content hash, exact-match snippets, contradiction matches, and a conservative verdict. Each source check costs **$0.01**. No API key, browser session, proxy, or language model is required. SourceReceipt is not a search engine, a semantic fact checker, or a truth oracle: it reports exactly what the live source supports, contradicts, or cannot establish under the rules supplied by the caller. ### When to use SourceReceipt - verify that a source or citation is still reachable before an AI agent acts; - check whether required wording, numbers, dates, or eligibility terms remain on the live page; - catch explicit contradiction terms such as `closed`, `expired`, `discontinued`, or `no longer available`; - enforce a content-freshness limit when the page declares a date; - create an auditable receipt with snippets, redirects, metadata, and a SHA-256 content hash for an agent workflow, API integration, or MCP-discovered tool. To run it, add one to twenty public URLs, define the exact terms that must or must not appear, optionally set `maxAgeDays`, and start the Actor. One structured dataset item is returned for each checked source. ### Why this is different Generic crawlers return page content and leave the caller to decide whether it is current or actually contains the required evidence. SourceReceipt makes that last mile deterministic: - `supported` - the page is reachable, every explicit rule passes, and any requested freshness can be verified; - `contradicted` - a forbidden term such as `closed`, `expired`, or `discontinued` appears; - `stale` - the content rules pass but the declared date exceeds the caller's maximum age; - `insufficient` - a required term or requested date signal is missing; - `unreachable` - the URL, response, redirect chain, content type, or size could not be safely verified. The caller supplies exact `mustContainAll`, `mustContainAny`, and `mustNotContain` terms. The free-form `claim` is a label for humans and is never silently interpreted by a model. ### Example input ```json { "targets": [ { "url": "https://example.com/program-rules", "label": "Program deadline", "claim": "The program remains open and offers a $100,000 cash pool.", "mustContainAll": ["$100,000"], "mustContainAny": ["applications are open", "entries are open"], "mustNotContain": ["closed", "expired", "cancelled"], "maxAgeDays": 30 } ], "timeoutSeconds": 20, "maxResponseBytes": 1000000, "snippetChars": 240, "concurrency": 4 } ```` ### Example output ```json { "targetIndex": 0, "label": "Program deadline", "requestedUrl": "https://example.com/program-rules", "finalUrl": "https://example.com/program-rules", "httpStatus": 200, "verdict": "supported", "freshnessStatus": "fresh", "declaredDate": "2026-07-10T09:30:00.000Z", "contentHashSha256": "...", "responseBytes": 41238, "ruleSummary": { "allRequiredMatched": true, "anyRequiredMatched": true, "forbiddenMatched": false, "missingAll": [], "missingAny": [], "matchedForbidden": [] }, "evidence": [ { "kind": "required_all", "term": "$100,000", "snippet": "...verified cash pool is $100,000...", "position": 148 } ] } ``` ### Safety and privacy - SourceReceipt is an independent utility. It is not affiliated with, endorsed by, or sponsored by any website a user chooses to check. - Only public HTTP(S) pages are accepted. - URL credentials, localhost, internal hostnames, and private, reserved, link-local, multicast, or otherwise non-public IP addresses are rejected. - Every redirect destination is resolved and checked again. - Responses have hard time and byte limits. - Only supported text, HTML, XML, and JSON content is read. - Scripts are never executed. Script, style, template, SVG, and canvas content is removed before matching. - Output contains only short matching snippets, not a full copied page. - No API key, LLM call, browser session, customer credential, or personal data is required. ### Marketplace economics SourceReceipt uses Apify Store pay-per-event pricing. One explicit `source-receipt` event costs **$0.01 per checked source** ($10 per 1,000), with platform usage included in the price. Apify documents profit as 80% of event revenue minus platform costs, so the pre-cost creator share is $0.008 per receipt. A low-priced synthetic `apify-actor-start` event costs $0.00005 per run. `apify-default-dataset-item` is not configured; the runtime fails closed if a second result event could double charge a receipt. The Actor uses no browser, proxy, or paid model, defaults to 256 MB, and is capped at 512 MB. The private owner benchmark below establishes the measured cost boundary; it is not customer demand or revenue evidence. SourceReceipt runs with limited permissions and Standby disabled. The account has completed the payout eligibility gate. The one owner benchmark remains cost evidence, not demand or revenue evidence. ### Local verification ```powershell npm ci npm run verify npm run preflight npx --yes apify-cli@1.7.1 validate-schema npm run demo npm run benchmark ``` `npm run demo` performs one read-only request to `https://example.com/` and prints the resulting receipt. Unit tests use injected responses and do not depend on live websites. #### Local PPE boundary test The following uses Apify's documented local PPE test mode, where each test event is modeled at $1. A three-target run with a $2 cap must fetch, emit, and log exactly two receipts: ```powershell $env:ACTOR_TEST_PAY_PER_EVENT = "true" $env:ACTOR_USE_CHARGING_LOG_DATASET = "true" $env:ACTOR_MAX_TOTAL_CHARGE_USD = "2" npx --yes apify-cli@1.7.1 run --purge --input-file demo/ppe-input.json ``` The verified 16 July 2026 run produced two default-dataset items and two `source-receipt` charging-log items. The third target was omitted before its network request, proving the charge cap bounds work as well as output. #### Local live cost preflight `npm run benchmark` performs three bounded runs across ten varied public pages and writes the full evidence to `var/source-receipt/local-benchmark.json`. The 16 July 2026 preflight measured a 388 ms median wall time per ten receipts, 25.8 receipts/second median throughput, and 161 MB maximum RSS. Eight pages were supported and two conservatively returned unreachable (one oversized response and one page with no extractable server text). Using current documented Bronze rates, 256 MB memory, decoded response bytes with a 25% transfer safety factor, a two-times runtime multiplier, storage operations, and the five-second synthetic-start compute credit, the worst modeled platform cost was **$0.0000227 per receipt**. That conservative model is now bracketed by the measured private-cloud result below. #### Private cloud cost evidence On 16 July 2026, one private owner run used the 256 MB configuration and finished in 6.06 seconds. It returned all ten schema-compatible receipts: eight supported and two unreachable, matching the local benchmark's conservative outcomes. The run processed 621,794 response bytes, consumed 0.000410069 compute units, and reported **$0.000188695** total platform usage, or **$0.00001887 per receipt**. Against the $0.008 pre-cost creator share, that measured usage leaves about **$0.007981 per receipt** before maintenance time and payout effects, a 99.76% unit margin on the creator share. This clears the private cost/output gate. It does not establish willingness to pay, a paying customer, or revenue. ### Marketplace evidence, not revenue evidence Public Apify Store data checked on 16 July 2026 showed substantial existing agent demand for web inputs: the official RAG Web Browser reported about 27,000 users in the preceding 30 days and the official Website Content Crawler about 8,000. Apify documents native Store discovery, pay-per-event billing, an 80% creator share before platform costs, and automatic eligibility for agentic payments when a limited-permission PPE Actor meets its rules. That is evidence for the distribution surface, not proof that SourceReceipt will sell. The experiment is successful only after paid runs from users other than the owner produce verified positive net revenue. ### Maintenance boundary Dynamic, client-rendered pages may expose too little server HTML. SourceReceipt returns `insufficient` with a warning rather than adding a costly browser tier or pretending the content was observed. A browser-backed tier should be added only if paid usage proves the need. # Actor input Schema ## `targets` (type: `array`): One to twenty public HTTP(S) pages. Each target can require all terms, at least one alternative term, forbid contradiction terms, and optionally require a declared content date within a maximum age. ## `timeoutSeconds` (type: `integer`): Hard network timeout per redirect hop. ## `maxResponseBytes` (type: `integer`): Stops oversized responses before they consume unbounded memory. ## `snippetChars` (type: `integer`): Maximum characters retained around each exact term match. ## `concurrency` (type: `integer`): Bounded parallel checks per run. ## Actor input object example ```json { "targets": [ { "url": "https://example.com/", "label": "Default evidence check", "claim": "The live page is the Example Domain page.", "mustContainAll": [ "Example Domain" ], "mustNotContain": [ "expired" ] } ], "timeoutSeconds": 20, "maxResponseBytes": 1000000, "snippetChars": 240, "concurrency": 4 } ``` # Actor output Schema ## `results` (type: `string`): Structured source-verification verdicts, exact-match evidence snippets, dates, redirects, and content hashes. # 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 = { "targets": [ { "url": "https://example.com/", "label": "Default evidence check", "claim": "The live page is the Example Domain page.", "mustContainAll": [ "Example Domain" ], "mustNotContain": [ "expired" ] } ] }; // Run the Actor and wait for it to finish const run = await client.actor("sassy_labs/source-receipt-evidence-gate").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 = { "targets": [{ "url": "https://example.com/", "label": "Default evidence check", "claim": "The live page is the Example Domain page.", "mustContainAll": ["Example Domain"], "mustNotContain": ["expired"], }] } # Run the Actor and wait for it to finish run = client.actor("sassy_labs/source-receipt-evidence-gate").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 '{ "targets": [ { "url": "https://example.com/", "label": "Default evidence check", "claim": "The live page is the Example Domain page.", "mustContainAll": [ "Example Domain" ], "mustNotContain": [ "expired" ] } ] }' | apify call sassy_labs/source-receipt-evidence-gate --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=sassy_labs/source-receipt-evidence-gate", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SourceReceipt - Source Verification for AI Agents", "description": "Verify sources and citations before AI agents act. Check public URLs for required, contradictory, or stale evidence and return structured receipts with exact snippets, redirects, dates, and SHA-256 hashes.", "version": "0.1", "x-build-id": "9vLjxBowBbQj2fYNP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/sassy_labs~source-receipt-evidence-gate/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-sassy_labs-source-receipt-evidence-gate", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/sassy_labs~source-receipt-evidence-gate/runs": { "post": { "operationId": "runs-sync-sassy_labs-source-receipt-evidence-gate", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/sassy_labs~source-receipt-evidence-gate/run-sync": { "post": { "operationId": "run-sync-sassy_labs-source-receipt-evidence-gate", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "targets" ], "properties": { "targets": { "title": "Evidence targets", "minItems": 1, "maxItems": 20, "type": "array", "description": "One to twenty public HTTP(S) pages. Each target can require all terms, at least one alternative term, forbid contradiction terms, and optionally require a declared content date within a maximum age.", "items": { "type": "object", "additionalProperties": false, "properties": { "url": { "title": "Public URL", "description": "HTTP(S) page to verify. Local, private-network, credential-bearing, and non-web URLs are rejected.", "type": "string", "editor": "textfield", "minLength": 8, "maxLength": 2048 }, "label": { "title": "Label", "description": "Short name for this evidence target.", "type": "string", "editor": "textfield", "maxLength": 120 }, "claim": { "title": "Claim under review", "description": "Human-readable context only. The verdict is based on the explicit term rules below, not semantic interpretation of this text.", "type": "string", "editor": "textarea", "maxLength": 1000 }, "mustContainAll": { "title": "Every term required", "description": "Every listed term must appear in normalized visible page text.", "type": "array", "editor": "stringList", "maxItems": 20, "items": { "type": "string", "minLength": 1, "maxLength": 500 } }, "mustContainAny": { "title": "At least one term required", "description": "If supplied, at least one listed alternative must appear.", "type": "array", "editor": "stringList", "maxItems": 20, "items": { "type": "string", "minLength": 1, "maxLength": 500 } }, "mustNotContain": { "title": "Contradiction terms", "description": "A match produces a contradicted verdict, for example closed, expired, discontinued, or no longer available.", "type": "array", "editor": "stringList", "maxItems": 20, "items": { "type": "string", "minLength": 1, "maxLength": 500 } }, "maxAgeDays": { "title": "Maximum declared age in days", "description": "Optional freshness requirement based on page metadata or the HTTP Last-Modified header. Missing date evidence is reported as insufficient, never guessed.", "type": "integer", "editor": "number", "minimum": 0, "maximum": 3650 } }, "required": [ "url" ] } }, "timeoutSeconds": { "title": "Timeout per request", "minimum": 3, "maximum": 60, "type": "integer", "description": "Hard network timeout per redirect hop.", "default": 20 }, "maxResponseBytes": { "title": "Maximum response bytes", "minimum": 10000, "maximum": 5000000, "type": "integer", "description": "Stops oversized responses before they consume unbounded memory.", "default": 1000000 }, "snippetChars": { "title": "Evidence snippet length", "minimum": 80, "maximum": 500, "type": "integer", "description": "Maximum characters retained around each exact term match.", "default": 240 }, "concurrency": { "title": "Concurrent checks", "minimum": 1, "maximum": 6, "type": "integer", "description": "Bounded parallel checks per run.", "default": 4 } } }, "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 } } } } } } } } } } ```