# Zentra Agent Incident Scribe (`zentrafoundry/zentra-agent-incident-scribe`) Actor Generate clean incident reports from agent and Actor failure evidence. - **URL**: https://apify.com/zentrafoundry/zentra-agent-incident-scribe.md - **Developed by:** [Zentra](https://apify.com/zentrafoundry) (community) - **Categories:** AI, Agents, Developer tools - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $10.00 / 1,000 result delivereds 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 ## Zentra Agent Incident Scribe Generate clean incident reports from agent and Actor failure evidence. ### Make agents earn more ### 1. One-sentence promise Write incident reports from evidence, not guesswork. ### 2. When to use this Actor Use this Actor when Agent operators, support teams, platform owners needs Convert failure evidence into timeline, impact, cause, and remediation. and a buyer-visible AgentOps artifact before any pay-per-event charge is recorded. ### 3. When not to use this Actor Do not use this Actor as a legal, security, compliance, revenue, or incident certification system. Findings are deterministic signals, not a legal, security, or compliance certification. Review high-impact decisions before blocking production workflows. ### 4. Inputs table | Input | Purpose | | --- | --- | | `inlineItems` | Inline records, traces, runs, events, manifests, or scenario artifacts supplied directly by the buyer. | | `sourceDatasets` | Optional user-selected Apify datasets. | | `sourceKeyValueStores` | Optional user-selected Apify key-value stores. | | `actorJson`, `inputSchemaJson`, `outputSchemaJson`, `readmeText` | Actor/package metadata used by policy, passport, audit, and repair flows. | | `connectorManifests` | Optional MCP connector/tool definitions for policy linting. | | `logText`, `runMetadata`, `inputJson`, `outputJson` | Explicit run artifacts used for audit, repair, cost, or incident reports. | | `scenarios`, `inlineTraces`, `inlineRuns`, `inlineEvents`, `toolCall` | Actor-specific artifacts for monitor, trace, cost, incident, and firewall outputs. | | `notificationConnectors`, `destinationConnectors` | Optional user-supplied MCP writeback connectors. Destructive actions are not automatic. | | `dryRun`, `maxArtifacts` | PPE control fields for would-charge ledgers and low-cost buyer trials. | ### 5. Output datasets table The generated Actor config exposes these dataset aliases: ```json [ "default", "timeline", "findings", "evidence", "remediations", "actions" ] ```` Every successful run also writes a default dataset row containing the summary, confidence, evidence hash, preflight quote, would-charge ledger, and earnings report. ### 6. Example input JSON ```json { "incidentTitle": "Agent workflow failed during connector writeback", "logText": "403 forbidden while posting update", "inlineEvents": [ { "timestamp": "2026-06-18T00:00:00Z", "message": "writeback denied" } ], "redactSecrets": true } ``` ### 7. Example output rows ```json { "actorSlug": "zentra-agent-incident-scribe", "status": "artifact_ready", "summary": "Buyer-visible AgentOps artifact produced.", "artifact": { "kind": "agentops_result", "evidence": { "redactionApplied": true } }, "runSummary": { "pricingModel": "PAY_PER_EVENT", "wouldChargeEventCount": 1 } } ``` Actor-specific datasets include findings, evidence, clean/quarantine rows, policy packs, audit metrics, scenario results, normalized spans, policy decisions, repair steps, cost events, or incident timelines depending on the selected AgentOps Actor. ### 8. Privacy and permission notes This Actor is designed for limited permissions. It can read only its own run storages and user-provided resources selected in the input form. Optional MCP connectors are supplied by the user at runtime through Apify's connector proxy; the Actor does not receive raw third-party credentials. Secret-looking values are redacted before snippets are stored in evidence rows. Evidence datasets store hashes, redacted snippets, counts, and field paths instead of raw credentials or full logs. ### 9. PPE pricing notes Pricing model: `PAY_PER_EVENT`. - `incident-report-created`: $0.5000 after one incident report - `timeline-extracted`: $0.1200 after one ordered incident timeline - `remediation-plan`: $0.2500 after one prevention plan The Actor writes `preflightQuote.json` before paid work and `agentEarningsReport.json` after the run. Dry runs produce a would-charge ledger without billing. Internal validation runs, canary runs, synthetic checks, and forecasts are not buyer revenue. Buyer-visible charged events are the revenue truth. ### 10. Troubleshooting - If the Actor reports `ppe-disabled`, set `ZENTRA_ENABLE_PPE=1` only in the real paid Apify environment. - If connector findings are high or critical, reduce connector scope before exposing the tool to autonomous agents. - If no source artifacts are supplied, the Actor runs a deterministic sample so the output contract remains inspectable. - If a writeback connector fails, review the `actions` dataset. The core artifact remains valid. ### 11. Changelog - `1.0.0`: Initial reconciled Zentra AgentOps public Actor package with limited permissions, multiple dataset outputs, evidence hashing, dry-run PPE ledger, and owner-gated publication flow. # Actor input Schema ## `buyerQuery` (type: `string`): Buyer-safe query or scope for the records returned by this product. ## `taskIntent` (type: `string`): Stable product-specific purpose for this saved Apify task. ## `sourceMode` (type: `string`): Sample emits public-safe Apify Actor Record rows. Approved live source mode keeps the same output fields and only uses owner-approved public URLs. ## `outputMode` (type: `string`): Use sample records for Apify Store QA or buyer-ready records for approved Apify Actor Record delivery. ## `startUrls` (type: `array`): Public URLs to use for live Apify Actor Record extraction after source-policy approval. Leave empty for sample mode. ## `maxItems` (type: `integer`): Caps the number of Apify Actor Record rows written to the dataset. ## `perSourceLimit` (type: `integer`): Caps validated rows from any one source before cross-source deduplication. ## `maxTotalChargeUsd` (type: `number`): Buyer-selected spend ceiling; the Apify run-level maximum remains authoritative. ## `overallTimeoutSecs` (type: `integer`): Stops additional source work once the bounded run deadline is reached. ## `requestTimeoutSecs` (type: `integer`): Timeout applied independently to each approved source request. ## `maxRequestRetries` (type: `integer`): Bounded retry count for transient source failures. ## `sinceLastRun` (type: `boolean`): Uses stable Actor state to skip logical records delivered by earlier runs. ## `deltaMode` (type: `boolean`): Preserves stable deduplication keys for recurring tasks and schedules. ## Actor input object example ```json { "buyerQuery": "buyer-ready records with source evidence", "taskIntent": "buyer-ready-product-run", "sourceMode": "sample", "outputMode": "sample-records", "startUrls": [], "maxItems": 1, "perSourceLimit": 25, "maxTotalChargeUsd": 5, "overallTimeoutSecs": 900, "requestTimeoutSecs": 30, "maxRequestRetries": 2, "sinceLastRun": false, "deltaMode": true } ``` # 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 = { "buyerQuery": "buyer-ready records with source evidence", "taskIntent": "buyer-ready-product-run", "sourceMode": "sample", "outputMode": "sample-records", "startUrls": [], "maxItems": 1, "perSourceLimit": 25, "maxTotalChargeUsd": 5, "overallTimeoutSecs": 900, "requestTimeoutSecs": 30, "maxRequestRetries": 2, "sinceLastRun": false, "deltaMode": true }; // Run the Actor and wait for it to finish const run = await client.actor("zentrafoundry/zentra-agent-incident-scribe").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 = { "buyerQuery": "buyer-ready records with source evidence", "taskIntent": "buyer-ready-product-run", "sourceMode": "sample", "outputMode": "sample-records", "startUrls": [], "maxItems": 1, "perSourceLimit": 25, "maxTotalChargeUsd": 5, "overallTimeoutSecs": 900, "requestTimeoutSecs": 30, "maxRequestRetries": 2, "sinceLastRun": False, "deltaMode": True, } # Run the Actor and wait for it to finish run = client.actor("zentrafoundry/zentra-agent-incident-scribe").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 '{ "buyerQuery": "buyer-ready records with source evidence", "taskIntent": "buyer-ready-product-run", "sourceMode": "sample", "outputMode": "sample-records", "startUrls": [], "maxItems": 1, "perSourceLimit": 25, "maxTotalChargeUsd": 5, "overallTimeoutSecs": 900, "requestTimeoutSecs": 30, "maxRequestRetries": 2, "sinceLastRun": false, "deltaMode": true }' | apify call zentrafoundry/zentra-agent-incident-scribe --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=zentrafoundry/zentra-agent-incident-scribe", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zentra Agent Incident Scribe", "description": "Generate clean incident reports from agent and Actor failure evidence.", "version": "1.0", "x-build-id": "p6D9hICgudj7Ec2vY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/zentrafoundry~zentra-agent-incident-scribe/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-zentrafoundry-zentra-agent-incident-scribe", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/zentrafoundry~zentra-agent-incident-scribe/runs": { "post": { "operationId": "runs-sync-zentrafoundry-zentra-agent-incident-scribe", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/zentrafoundry~zentra-agent-incident-scribe/run-sync": { "post": { "operationId": "run-sync-zentrafoundry-zentra-agent-incident-scribe", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "sourceMode" ], "properties": { "buyerQuery": { "title": "Apify Actor Record query", "type": "string", "description": "Buyer-safe query or scope for the records returned by this product.", "default": "buyer-ready records with source evidence" }, "taskIntent": { "title": "Apify Actor Record task intent", "type": "string", "description": "Stable product-specific purpose for this saved Apify task.", "default": "buyer-ready-product-run" }, "sourceMode": { "title": "Run sample or approved live sources", "enum": [ "sample", "startUrls" ], "type": "string", "description": "Sample emits public-safe Apify Actor Record rows. Approved live source mode keeps the same output fields and only uses owner-approved public URLs.", "default": "sample" }, "outputMode": { "title": "Apify Actor Record output mode", "enum": [ "sample-records", "buyer-ready-records" ], "type": "string", "description": "Use sample records for Apify Store QA or buyer-ready records for approved Apify Actor Record delivery.", "default": "sample-records" }, "startUrls": { "title": "Approved Apify Actor Record source URLs", "type": "array", "description": "Public URLs to use for live Apify Actor Record extraction after source-policy approval. Leave empty for sample mode.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "title": "URL", "type": "string", "description": "Approved public Apify Actor Record source URL." } } }, "default": [] }, "maxItems": { "title": "Maximum Apify Actor Record rows", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Caps the number of Apify Actor Record rows written to the dataset.", "default": 1 }, "perSourceLimit": { "title": "Maximum rows per source", "minimum": 1, "maximum": 100, "type": "integer", "description": "Caps validated rows from any one source before cross-source deduplication.", "default": 25 }, "maxTotalChargeUsd": { "title": "Maximum total charge (USD)", "minimum": 0.01, "maximum": 1000, "type": "number", "description": "Buyer-selected spend ceiling; the Apify run-level maximum remains authoritative.", "default": 5 }, "overallTimeoutSecs": { "title": "Overall timeout seconds", "minimum": 30, "maximum": 3600, "type": "integer", "description": "Stops additional source work once the bounded run deadline is reached.", "default": 900 }, "requestTimeoutSecs": { "title": "Source request timeout seconds", "minimum": 5, "maximum": 120, "type": "integer", "description": "Timeout applied independently to each approved source request.", "default": 30 }, "maxRequestRetries": { "title": "Maximum source retries", "minimum": 0, "maximum": 5, "type": "integer", "description": "Bounded retry count for transient source failures.", "default": 2 }, "sinceLastRun": { "title": "Only emit new logical records", "type": "boolean", "description": "Uses stable Actor state to skip logical records delivered by earlier runs.", "default": false }, "deltaMode": { "title": "Delta mode", "type": "boolean", "description": "Preserves stable deduplication keys for recurring tasks and schedules.", "default": 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 } } } } } } } } } } ```