# ðŸĨ Clinical Trials Scraper (`taroyamada/clinical-trials-pipeline-monitor`) Actor Extract and monitor clinical trial data from ClinicalTrials.gov to track new studies, recruitment updates, and targeted conditions using automated watchlist queries. - **URL**: https://apify.com/taroyamada/clinical-trials-pipeline-monitor.md - **Developed by:** [åĪŠéƒŽ åąąį”°](https://apify.com/taroyamada) (community) - **Categories:** Business, Automation, Lead generation - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 results 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 ## Clinical Trials Monitor | Condition & Recruitment Watch Monitor ClinicalTrials.gov for new and updated studies matching condition keywords and recruitment status — one digest row per configured watchlist query without brittle broad crawling. ### Store Quickstart Run this actor with your target input. Results appear in the Apify Dataset and can be piped to webhooks for real-time delivery. Use `dryRun` to validate before committing to a schedule. ### Key Features - 📈 **Competitive intelligence** — Aggregates cross-platform signals (reviews, listings, catalogs) - 🌐 **Multi-source aggregation** — Unifies iOS/Android/Shopify/market data in one run - 📊 **Trend detection** — Rolling averages, sentiment scoring, and share-of-voice metrics - ðŸŽŊ **Targeted queries** — Focused brand/product/keyword watchlists - ðŸ“Ą **Webhook intel push** — Deliver insights to marketing/product teams in real-time ### Use Cases | Who | Why | |-----|-----| | Developers | Automate recurring data fetches without building custom scrapers | | Data teams | Pipe structured output into analytics warehouses | | Ops teams | Monitor changes via webhook alerts | | Product managers | Track competitor/market signals without engineering time | ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | watchlist | array | **required** | One entry per monitored query. Each produces one digest row in the output. At minimum set id, name, and condition. Add r | | watchTerms | string | — | Sponsor names, principal investigators, or institution names to flag in study digests. Any study matching a watch term r | | maxStudiesPerQuery | integer | `50` | Upper bound on studies fetched per query per run. Increase for discovery; keep lower for recurring digest runs. | | delivery | string | `"dataset"` | dataset stores results in the Apify dataset. webhook posts the digest JSON to webhookUrl. | | webhookUrl | string | — | POST target for trial digest payload. Leave empty for dataset delivery. | | datasetMode | string | `"all"` | all emits every query digest row. action_needed emits only queries with watch-term hits or new recruiting studies. new_o | | snapshotKey | string | `"clinical-trials-monitor-state"` | Stable key used to persist seen study NCT IDs across recurring runs so new_only and action_needed modes stay comparable. | | clinicalTrialsApiUrl | string | `"https://clinicaltrials.gov/api/v2/studies"` | ClinicalTrials.gov API v2 studies endpoint. No API key required. | #### Input Example ```json { "maxStudiesPerQuery": 50, "delivery": "dataset", "datasetMode": "all", "snapshotKey": "clinical-trials-monitor-state", "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies", "requestTimeoutSeconds": 30, "notifyOnNoNew": true, "dryRun": false } ```` ### Output | Field | Type | Description | |-------|------|-------------| | `meta` | object | | | `errors` | array | | | `digests` | array | | | `digests[].queryId` | string | | | `digests[].queryName` | string | | | `digests[].condition` | string | | | `digests[].recruitmentStatusFilter` | array | | | `digests[].checkedAt` | timestamp | | | `digests[].status` | string | | | `digests[].newStudyCount` | number | | | `digests[].totalStudyCount` | number | | | `digests[].recruitingCount` | number | | | `digests[].changedSinceLastRun` | boolean | | | `digests[].actionNeeded` | boolean | | | `digests[].recommendedAction` | string | | | `digests[].topSponsors` | array | | | `digests[].watchTermHits` | array | | | `digests[].signalTags` | array | | | `digests[].studies` | array | | | `digests[].error` | null | | #### Output Example ```json { "meta": { "generatedAt": "2026-04-15T09:00:00.000Z", "now": "2026-04-15T09:00:00.000Z", "queryCount": 2, "totalStudies": 7, "newStudies": 4, "watchTermHitCount": 2, "actionNeededCount": 1, "snapshot": { "key": "clinical-trials-monitor-sample", "loadedFrom": "local", "savedTo": "local" }, "warnings": [], "executiveSummary": { "overallStatus": "action_needed", "brief": "1 query(s) have sponsor watch-term hits requiring review.", "topSponsors": [ { "name": "Pfizer Inc", "studyCount": 2, "isWatchTermHit": true }, { "name": "Novo Nordisk A/S", "studyCount": 1, "isWatchTermHit": true }, { "name": "AstraZeneca", "studyCount": 2, "isWatchTermHit": false } ], "watchTermHits": [ { "term": "Pfizer", "studyId": "NCT05001234", "sponsor": "Pfizer Inc", ``` ### API Usage Run this actor programmatically using the Apify API. Replace `YOUR_API_TOKEN` with your token from [Apify Console → Settings → Integrations](https://console.apify.com/account/integrations). #### cURL ```bash curl -X POST "https://api.apify.com/v2/acts/taroyamada~clinical-trials-pipeline-monitor/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "maxStudiesPerQuery": 50, "delivery": "dataset", "datasetMode": "all", "snapshotKey": "clinical-trials-monitor-state", "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies", "requestTimeoutSeconds": 30, "notifyOnNoNew": true, "dryRun": false }' ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("taroyamada/clinical-trials-pipeline-monitor").call(run_input={ "maxStudiesPerQuery": 50, "delivery": "dataset", "datasetMode": "all", "snapshotKey": "clinical-trials-monitor-state", "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies", "requestTimeoutSeconds": 30, "notifyOnNoNew": true, "dryRun": false }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` #### JavaScript / Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_API_TOKEN' }); const run = await client.actor('taroyamada/clinical-trials-pipeline-monitor').call({ "maxStudiesPerQuery": 50, "delivery": "dataset", "datasetMode": "all", "snapshotKey": "clinical-trials-monitor-state", "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies", "requestTimeoutSeconds": 30, "notifyOnNoNew": true, "dryRun": false }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Tips & Limitations - Run weekly for trend tracking; daily for competitive launch monitoring. - Use webhook delivery to push insights into your BI tools or marketing Slack. - Archive results in Apify Dataset for your own historical trend analysis. - Combine with `ai-visibility-monitor-actor` for AI-era brand surface coverage. - Start with a small watchlist, iterate on keyword precision before scaling. ### FAQ **What platforms are covered?** Varies by actor — see each actor's input schema for the full source list. Most cover 3–8 major platforms per vertical. **How is data deduplicated across sources?** The actor normalizes entity identifiers (brand name, SKU) before aggregation — cross-source duplicates are merged. **Can I whitelabel the output?** Dataset rows are raw data — build your own presentation layer to whitelabel. **Is the sentiment scoring accurate?** Sentiment uses rule-based + keyword scoring tuned for English. For non-English content, treat scores as directional rather than absolute. **Can I share the dashboard output?** Export from Dataset API into your BI tool (Looker, Metabase, Tableau) for stakeholder-facing dashboards. ### Related Actors Market Intelligence cluster — explore related Apify tools: - [AI Brand Visibility Monitor API | Google + Reddit Tracker](https://apify.com/taroyamada/ai-visibility-monitor-actor) — See whether your AI brand is appearing, climbing, or disappearing in Google and Reddit prompts, then get rank deltas, competitor overlap, and weekly action items. - [Shopify Store Intelligence API | Catalog + Merch Signals](https://apify.com/taroyamada/shopify-store-intelligence) — Analyze public Shopify storefront endpoints for store metadata, collections, product samples, and vendor/tag rollups. - [App Review Intelligence API | App Store + Google Play Summary](https://apify.com/taroyamada/app-review-cross-platform-intelligence) — Monitor one app across the App Store and Google Play, cluster review themes, flag rating drift, and return recommended actions in a single summary row. - [TED, SAM.gov & Grants Monitor | Bid Alerts & Award Watch](https://apify.com/taroyamada/procurement-intel-actor) — Public-sector tender monitoring for teams that need TED, SAM. ### Cost **Pay Per Event**: - `actor-start`: $0.01 (flat fee per run) - `dataset-item`: $0.003 per output item **Example**: 1,000 items = $0.01 + (1,000 × $0.003) = **$3.01** No subscription required — you only pay for what you use. # Actor input Schema ## `watchlist` (type: `array`): One entry per monitored query. Each produces one digest row in the output. At minimum set id, name, and condition. Add recruitmentStatus to narrow the result stream. ## `watchTerms` (type: `string`): Sponsor names, principal investigators, or institution names to flag in study digests. Any study matching a watch term receives a watch\_term\_hit signal tag. ## `maxStudiesPerQuery` (type: `integer`): Upper bound on studies fetched per query per run. Increase for discovery; keep lower for recurring digest runs. ## `delivery` (type: `string`): dataset stores results in the Apify dataset. webhook posts the digest JSON to webhookUrl. ## `webhookUrl` (type: `string`): POST target for trial digest payload. Leave empty for dataset delivery. ## `datasetMode` (type: `string`): all emits every query digest row. action\_needed emits only queries with watch-term hits or new recruiting studies. new\_only emits only queries with studies not seen in the previous run. ## `snapshotKey` (type: `string`): Stable key used to persist seen study NCT IDs across recurring runs so new\_only and action\_needed modes stay comparable. Use the same key across scheduled runs. ## `clinicalTrialsApiUrl` (type: `string`): ClinicalTrials.gov API v2 studies endpoint. No API key required. ## `requestTimeoutSeconds` (type: `integer`): Timeout for each API request. ## `notifyOnNoNew` (type: `boolean`): When true, every query always produces a digest row even if no new studies were found. When false, queries with no new studies are omitted. ## `dryRun` (type: `boolean`): Validate and fetch without persisting state or posting webhooks. Safe for testing input shapes. ## `nowIso` (type: `string`): Set to a fixed ISO timestamp to make runs deterministic against fixture data. ## `fixtureDir` (type: `string`): Directory containing JSON fixture files for offline tests. Files should be named .json. ## Actor input object example ```json { "maxStudiesPerQuery": 50, "delivery": "dataset", "datasetMode": "all", "snapshotKey": "clinical-trials-monitor-state", "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies", "requestTimeoutSeconds": 30, "notifyOnNoNew": true, "dryRun": false } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("taroyamada/clinical-trials-pipeline-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`ðŸ’ū 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 = {} # Run the Actor and wait for it to finish run = client.actor("taroyamada/clinical-trials-pipeline-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("ðŸ’ū 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 '{}' | apify call taroyamada/clinical-trials-pipeline-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=taroyamada/clinical-trials-pipeline-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ðŸĨ Clinical Trials Scraper", "description": "Extract and monitor clinical trial data from ClinicalTrials.gov to track new studies, recruitment updates, and targeted conditions using automated watchlist queries.", "version": "0.1", "x-build-id": "3dlyP28Nj1uk1jBG3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/taroyamada~clinical-trials-pipeline-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-taroyamada-clinical-trials-pipeline-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/taroyamada~clinical-trials-pipeline-monitor/runs": { "post": { "operationId": "runs-sync-taroyamada-clinical-trials-pipeline-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/taroyamada~clinical-trials-pipeline-monitor/run-sync": { "post": { "operationId": "run-sync-taroyamada-clinical-trials-pipeline-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "watchlist" ], "properties": { "watchlist": { "title": "Watchlist queries (required)", "type": "array", "description": "One entry per monitored query. Each produces one digest row in the output. At minimum set id, name, and condition. Add recruitmentStatus to narrow the result stream.", "items": { "type": "object", "properties": { "id": { "title": "Query ID", "description": "Stable identifier used in snapshots and output rows.", "type": "string" }, "name": { "title": "Query name", "description": "Human-readable label for this query in the digest output.", "type": "string" }, "condition": { "title": "Condition keyword", "description": "Condition or disease to search (maps to query.cond in the ClinicalTrials.gov API v2). Examples: 'diabetes', 'non-small cell lung cancer', 'alzheimer'.", "type": "string" }, "recruitmentStatus": { "title": "Recruitment status filter", "description": "Comma-separated recruitment statuses to include. Leave empty for all statuses. Valid values: RECRUITING, COMPLETED, ACTIVE_NOT_RECRUITING, ENROLLING_BY_INVITATION, NOT_YET_RECRUITING, SUSPENDED, TERMINATED, WITHDRAWN, AVAILABLE, NO_LONGER_AVAILABLE, TEMPORARILY_NOT_AVAILABLE, APPROVED_FOR_MARKETING, WITHHELD, UNKNOWN.", "type": "string" }, "intervention": { "title": "Intervention keyword", "description": "Optional intervention or drug name to narrow results (maps to query.intr).", "type": "string" }, "sponsor": { "title": "Sponsor name filter", "description": "Optional sponsor name fragment to narrow results (maps to query.spons).", "type": "string" }, "phase": { "title": "Phase filter", "description": "Comma-separated trial phases to include. Leave empty for all phases. Valid values: EARLY_PHASE1, PHASE1, PHASE2, PHASE3, PHASE4, NA.", "type": "string" } } } }, "watchTerms": { "title": "Watch terms — sponsor / PI / institution names (comma-separated)", "type": "string", "description": "Sponsor names, principal investigators, or institution names to flag in study digests. Any study matching a watch term receives a watch_term_hit signal tag." }, "maxStudiesPerQuery": { "title": "Max studies per query", "minimum": 1, "maximum": 200, "type": "integer", "description": "Upper bound on studies fetched per query per run. Increase for discovery; keep lower for recurring digest runs.", "default": 50 }, "delivery": { "title": "Delivery mode", "enum": [ "dataset", "webhook" ], "type": "string", "description": "dataset stores results in the Apify dataset. webhook posts the digest JSON to webhookUrl.", "default": "dataset" }, "webhookUrl": { "title": "Webhook URL (required when delivery=webhook)", "type": "string", "description": "POST target for trial digest payload. Leave empty for dataset delivery." }, "datasetMode": { "title": "Dataset output mode", "enum": [ "all", "action_needed", "new_only" ], "type": "string", "description": "all emits every query digest row. action_needed emits only queries with watch-term hits or new recruiting studies. new_only emits only queries with studies not seen in the previous run.", "default": "all" }, "snapshotKey": { "title": "Snapshot key for recurring state", "type": "string", "description": "Stable key used to persist seen study NCT IDs across recurring runs so new_only and action_needed modes stay comparable. Use the same key across scheduled runs.", "default": "clinical-trials-monitor-state" }, "clinicalTrialsApiUrl": { "title": "ClinicalTrials.gov API URL", "type": "string", "description": "ClinicalTrials.gov API v2 studies endpoint. No API key required.", "default": "https://clinicaltrials.gov/api/v2/studies" }, "requestTimeoutSeconds": { "title": "HTTP request timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "Timeout for each API request.", "default": 30 }, "notifyOnNoNew": { "title": "Emit digest even when no new studies found", "type": "boolean", "description": "When true, every query always produces a digest row even if no new studies were found. When false, queries with no new studies are omitted.", "default": true }, "dryRun": { "title": "Dry run (skip snapshot writes and webhook delivery)", "type": "boolean", "description": "Validate and fetch without persisting state or posting webhooks. Safe for testing input shapes.", "default": false }, "nowIso": { "title": "Override current time (ISO string, for testing)", "type": "string", "description": "Set to a fixed ISO timestamp to make runs deterministic against fixture data." }, "fixtureDir": { "title": "Fixture directory (testing)", "type": "string", "description": "Directory containing JSON fixture files for offline tests. Files should be named .json." } } }, "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 } } } } } } } } } } ```