# AI Reply Checker & Rewriter - ReplyGuard (`westerly_palisade/replyguard-by-dravara`) Actor Check an email, support reply, or customer message against its source conversation. Find missed questions, unsupported claims, unsafe promises, and tone risks; receive grounded findings and a conservative corrected reply. - **URL**: https://apify.com/westerly\_palisade/replyguard-by-dravara.md - **Developed by:** [Dravara LLC](https://apify.com/westerly_palisade) (community) - **Categories:** AI, Business, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.20 / reply analysis created 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## ReplyGuard **Check whether your reply addresses the conversation before you send it.** ReplyGuard compares a draft reply with the conversation it answers. It flags missed questions, accidental commitments, unsupported factual claims, ambiguous wording, repetition, and avoidable tone problems. A successful run returns structured findings plus a conservative corrected reply. ### Why use it - Add a pre-send quality gate to support, sales, or operations workflows. - Catch promises and dates that the received thread does not support. - Receive both JSON findings and copy-ready corrected text. - Run one bounded analysis through the Apify API, schedules, webhooks, or MCP. ### Input Provide `thread`, `proposed_reply`, and an optional tone of `preserve`, `warm`, `direct`, or `concise`. Questions in the thread do not establish their proposed answers as facts. ### Output The default dataset contains one item with `status`, `summary`, `findings`, and `corrected_reply`. Evidence is constrained to exact fragments from the input. When a generated correction cannot be validated, ReplyGuard supplies a neutral holding reply instead of guessing. ### Billing A successful run costs $0.20005: the $0.00005 `apify-actor-start` event plus $0.20 for `reply-analysis-created`. The result event is captured only after a result is available in the run dataset. Invalid inputs and provider failures skip the result charge, but the Actor-start charge can still apply. The synthetic sample input is billed like any other run. ### Privacy and limits Inputs are processed by Dravara, LLC's private service and the OpenAI API using `store: false`; applicable provider abuse-monitoring retention may still apply. Apify retains normal run input/output under the runner's plan and retention settings. Do not submit passwords, API keys, payment data, health data, or unrelated customer content. Maximum input sizes are 20,000 characters for the thread and 10,000 for the draft. No message is sent on the user's behalf. Support: [support@dravarahq.com](mailto:support@dravarahq.com) # Actor input Schema ## `thread` (type: `string`): The conversation context ReplyGuard should treat as the source of truth. ## `proposed_reply` (type: `string`): The draft that has not been sent. ## `tone` (type: `string`): Choose whether the corrected reply should preserve the draft's tone or shift toward a warm, direct, or concise style. ## Actor input object example ```json { "thread": "Can you confirm the final price and whether it will ship Friday?", "proposed_reply": "Yes, it will definitely ship Friday.", "tone": "preserve" } ```` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "thread": "Can you confirm the final price and whether it will ship Friday?", "proposed_reply": "Yes, it will definitely ship Friday." }; // Run the Actor and wait for it to finish const run = await client.actor("westerly_palisade/replyguard-by-dravara").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 = { "thread": "Can you confirm the final price and whether it will ship Friday?", "proposed_reply": "Yes, it will definitely ship Friday.", } # Run the Actor and wait for it to finish run = client.actor("westerly_palisade/replyguard-by-dravara").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 '{ "thread": "Can you confirm the final price and whether it will ship Friday?", "proposed_reply": "Yes, it will definitely ship Friday." }' | apify call westerly_palisade/replyguard-by-dravara --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=westerly_palisade/replyguard-by-dravara", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Reply Checker & Rewriter - ReplyGuard", "description": "Check an email, support reply, or customer message against its source conversation. Find missed questions, unsupported claims, unsafe promises, and tone risks; receive grounded findings and a conservative corrected reply.", "version": "1.1", "x-build-id": "y2X9bSRS96djwkqqD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/westerly_palisade~replyguard-by-dravara/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-westerly_palisade-replyguard-by-dravara", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/westerly_palisade~replyguard-by-dravara/runs": { "post": { "operationId": "runs-sync-westerly_palisade-replyguard-by-dravara", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/westerly_palisade~replyguard-by-dravara/run-sync": { "post": { "operationId": "run-sync-westerly_palisade-replyguard-by-dravara", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "thread", "proposed_reply" ], "properties": { "thread": { "title": "Original message or thread", "minLength": 1, "maxLength": 20000, "type": "string", "description": "The conversation context ReplyGuard should treat as the source of truth." }, "proposed_reply": { "title": "Proposed reply", "minLength": 1, "maxLength": 10000, "type": "string", "description": "The draft that has not been sent." }, "tone": { "title": "Preferred tone", "enum": [ "preserve", "warm", "direct", "concise" ], "type": "string", "description": "Choose whether the corrected reply should preserve the draft's tone or shift toward a warm, direct, or concise style.", "default": "preserve" } } }, "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 } } } } } } } } } } ```