# Ad-Guard AI: Global Compliance Audit Engine (`astilled/ad-guard-ai-global-compliance-audit-engine`) Actor Ban-proof your scaling. Instant, global ad & lander compliance audits powered by Llama 3.3 and Groq speed. Secure your accounts, scale safely. - **URL**: https://apify.com/astilled/ad-guard-ai-global-compliance-audit-engine.md - **Developed by:** [SoruvaLab](https://apify.com/astilled) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## 🛡️ Ad-Guard AI: Global Ad Compliance Audit Engine **Automated Ad Compliance.** Prevent ad account bans by auditing your copy against global standards. Fast, objective, and available 24/7. --- ### 🚀 Efficiency & Safety - **Llama 3.3 Powered:** Instant inference for high-speed audits. - **Data-Driven:** Clear risk scores based on global ad platform policies. - **Actionable:** Includes rewriting suggestions for non-compliant copy. --- ### 💰 Simple & Fair Pricing - **$1.00 per Audit Run** - **No Monthly Minimum / No Hidden Fees:** You only pay for what you use. - Ideal for both individual marketers and high-volume agencies. --- ### 🏢 B2B & Agency Solutions For professional teams and agencies, we offer a "Pay-As-You-Go" model for maximum flexibility. No expensive monthly commitments are required. - **Scale as you grow:** Whether you run 10 or 1,000 audits, you only pay **$1.00 per run**. - **API Integration:** Seamlessly integrate our engine into your internal dashboard or agency workflow via the Apify API. - **Custom Support:** For custom rulebook tailoring or large-scale enterprise needs, contact us. 👉 **Contact:** [hello@soruvalab.com](mailto:hello@soruvalab.com) --- ### 🛠️ How It Works 1. **Input:** Paste your ad copy and select the platform. 2. **Analysis:** The engine scans for policy violations (Medical, Financial, etc.). 3. **Output:** Instant audit report with a Risk Score and safe alternatives. --- ⚠️ Disclaimer: Ad-Guard AI is a guidance tool to minimize risk. Final ad approval rests with the platform (Meta, Google, TikTok, etc.). We are not liable for platform-side account actions. Use this as a strategic aid for your compliance workflow. *Global Market Ready. All prices in USD.* # Actor input Schema ## `platform` (type: `string`): Select the specific policy set to audit against. ## `content` (type: `string`): Paste the ad text or product description you want to audit. ## Actor input object example ```json { "platform": "meta_facebook", "content": "Get rich quick with this one simple trick! 100% guaranteed results." } ```` # Actor output Schema ## `auditResults` (type: `string`): The main audit report containing pass/fail status and policy violations. # 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 = { "content": "Get rich quick with this one simple trick! 100% guaranteed results." }; // Run the Actor and wait for it to finish const run = await client.actor("astilled/ad-guard-ai-global-compliance-audit-engine").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 = { "content": "Get rich quick with this one simple trick! 100% guaranteed results." } # Run the Actor and wait for it to finish run = client.actor("astilled/ad-guard-ai-global-compliance-audit-engine").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 '{ "content": "Get rich quick with this one simple trick! 100% guaranteed results." }' | apify call astilled/ad-guard-ai-global-compliance-audit-engine --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=astilled/ad-guard-ai-global-compliance-audit-engine", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Ad-Guard AI: Global Compliance Audit Engine", "description": "Ban-proof your scaling. Instant, global ad & lander compliance audits powered by Llama 3.3 and Groq speed. Secure your accounts, scale safely.", "version": "0.0", "x-build-id": "gHkAcKgBjmbGRfKih" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/astilled~ad-guard-ai-global-compliance-audit-engine/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-astilled-ad-guard-ai-global-compliance-audit-engine", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/astilled~ad-guard-ai-global-compliance-audit-engine/runs": { "post": { "operationId": "runs-sync-astilled-ad-guard-ai-global-compliance-audit-engine", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/astilled~ad-guard-ai-global-compliance-audit-engine/run-sync": { "post": { "operationId": "run-sync-astilled-ad-guard-ai-global-compliance-audit-engine", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "platform", "content" ], "properties": { "platform": { "title": "Audit Protocol", "enum": [ "meta_facebook", "instagram", "tiktok", "shopify", "general" ], "type": "string", "description": "Select the specific policy set to audit against.", "default": "meta_facebook" }, "content": { "title": "Ad Content / Copy", "type": "string", "description": "Paste the ad text or product description you want to audit." } } }, "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 } } } } } } } } } } ```