# Permit Signal Scout (`careybrown/permit-signal-scout`) Actor Normalize and rank public permit records into construction opportunity signals. - **URL**: https://apify.com/careybrown/permit-signal-scout.md - **Developed by:** [Carey Brown](https://apify.com/careybrown) (community) - **Categories:** Real estate, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results 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 ## Permit Signal Scout Permit Signal Scout turns selected official public building permit datasets into normalized, ranked construction opportunity signals. It reads public Socrata open-data endpoints, normalizes source-specific permit records into one schema, scores each record with deterministic rules, and reports source health so users can see whether the data feed behaved as expected. ### What It Does - Fetches recent public construction permit records from selected official city open-data sources. - Normalizes permit IDs, issue dates, permit types, descriptions, addresses, contractor/applicant/company names when available, estimated values, and statuses. - Classifies obvious trade signals such as roofing, HVAC, solar, plumbing, electrical, remodeling, ADU, multifamily, commercial, restoration, and general construction. - Scores records by freshness, estimated value, trade fit, and completeness. - Returns ranked permit opportunity signals with score reasons and risk flags. - Produces a run summary with per-source health. ### Who It Is For - Contractors watching for nearby project activity. - Construction suppliers monitoring demand signals. - Real estate investors tracking permit activity. - Agencies building research-backed prospect lists manually. - Data buyers who need normalized permit feeds from selected cities. ### Supported Sources / Cities | city id | city | source | dataset | |---|---|---|---| | `austin_tx` | Austin, TX | Austin Open Data | `3syk-w9eu` | | `chicago_il` | Chicago, IL | Chicago Data Portal | `ydr8-5enu` | | `nyc_ny` | New York City, NY | NYC Open Data DOB NOW | `rbx6-tga4` | | `cincinnati_oh` | Cincinnati, OH | Cincinnati Open Data | `uhjb-xac9` | | `san_francisco_ca` | San Francisco, CA | DataSF | `i98e-djp9` | ### What It Does Not Do - It does not find emails. - It does not verify owners or decision makers. - It does not guarantee contractor identity. - It does not send outreach. - It does not create ready-to-email lists. - It does not provide legal, compliance, or business advice. - It does not currently cover every city. - It does not use AI scoring in the MVP. - It does not perform contact enrichment, skip tracing, CRM sync, code-violation enrichment, or paid API calls. Permit Signal Scout provides permit opportunity signals, not verified sales leads. ### Example Use Cases - Find recent high-value roofing permits across the supported cities. - Monitor HVAC/mechanical permit activity in Austin and Chicago. - Compare recent permit volume and source health across all supported sources. - Pull raw normalized records for debugging a city adapter. - Build an internal research workflow around public permit activity. ### Input Fields | field | type | default | description | |---|---|---|---| | `cities` | string array | all supported cities | Source city IDs to query. | | `issuedAfter` | ISO date string | today minus 30 days | Include permits issued on or after this date. | | `issuedBefore` | ISO date string or null | null | Optional upper issued-date bound. | | `tradeKeywords` | string array | default trade terms | User keywords considered during trade matching. | | `minEstimatedValue` | number or null | null | Optional minimum estimated permit value. Records with null values are excluded when this is set. | | `maxResultsPerCity` | integer | 500 | Maximum records fetched per city, 1-5000. | | `includeAiScoring` | boolean | false | Reserved for later. MVP uses deterministic scoring and emits a warning if true. | | `outputMode` | string | `ranked` | Accepted values: `ranked`, `byCity`, `rawNormalized`. | | `includeRawRecord` | boolean | false | Include original Socrata row on each output record. | | `sortBy` | string | `leadQualityScore` | Accepted values: `leadQualityScore`, `issuedDate`, `estimatedValue`, `sourceCity`. | | `leadGradeFilter` | string array | `["A","B","C","D"]` | Return only selected lead grades after scoring. | ### Example Input ```json { "cities": ["austin_tx", "chicago_il", "nyc_ny"], "issuedAfter": "2026-05-01", "issuedBefore": null, "tradeKeywords": ["roof", "roofing", "reroof", "membrane"], "minEstimatedValue": 25000, "maxResultsPerCity": 250, "includeAiScoring": false, "outputMode": "ranked", "includeRawRecord": false, "sortBy": "leadQualityScore", "leadGradeFilter": ["A", "B"] } ```` More examples are in `examples/`. ### Output Fields Each output record follows this normalized shape: | field | description | |---|---| | `permitId` | Permit identifier from the source, or blank if missing. | | `sourceCity` | Source city ID. | | `sourceSystem` | Always `Socrata` for the MVP. | | `sourceDataset` | Socrata dataset ID. | | `sourceUrl` | Source record link when available or safely generated, otherwise null. | | `issuedDate` | Normalized ISO date or null. | | `permitType` | Normalized permit/work type text. | | `description` | Source work description. | | `address` | Normalized address text when available. | | `contractorName` | Contractor/applicant/company field when available and appropriate. | | `estimatedValue` | Parsed estimated value or null. | | `status` | Source permit status. | | `matchedTrades` | Matched trade categories or user keyword matches. | | `freshnessScore` | 0-100 issued-date freshness score. | | `valueScore` | 0-100 estimated-value score. | | `tradeFitScore` | 0-100 trade relevance score. | | `completenessScore` | 0-100 record completeness score. | | `leadQualityScore` | Weighted opportunity score rounded to one decimal. | | `leadGrade` | `A`, `B`, `C`, or `D`. | | `scoreReasons` | Concise explanation of why the record scored as it did. | | `riskFlags` | Missing/ambiguous/stale-data flags. | | `rawRecord` | Optional original source row when `includeRawRecord` is true. | ### Example Output ```json { "permitId": "SAMPLE-2026-001", "sourceCity": "austin_tx", "sourceSystem": "Socrata", "sourceDataset": "3syk-w9eu", "sourceUrl": "https://example.test/public-permit/SAMPLE-2026-001", "issuedDate": "2026-05-20", "permitType": "Building Permit / Roofing", "description": "Roof replacement and related exterior repair", "address": "123 SAMPLE ST", "contractorName": "SAMPLE ROOFING LLC", "estimatedValue": 45000.0, "status": "Issued", "matchedTrades": ["roofing"], "freshnessScore": 100, "valueScore": 75, "tradeFitScore": 100, "completenessScore": 100, "leadQualityScore": 93.8, "leadGrade": "A", "scoreReasons": [ "recent permit", "solid estimated value", "matched roofing trade", "complete record", "contractor/applicant present" ], "riskFlags": [] } ``` This is a synthetic example. It shows the output shape, not a verified sales lead. ### Run Summary The run summary reports: - `totalRecordsFetched` - `totalRecordsReturned` - `recordsByCity` - `averageLeadQualityScore` - `topMatchedTrades` - `sourceHealth` - `warnings` `examples/run_summary_sample.json` shows the expected shape. ### Scoring Model The MVP uses deterministic scoring only: ```text leadQualityScore = freshnessScore * 0.30 + valueScore * 0.25 + tradeFitScore * 0.25 + completenessScore * 0.20 ``` `leadQualityScore` is rounded to one decimal. Freshness score: - 0-7 days old: 100 - 8-30 days old: 85 - 31-90 days old: 65 - 91-180 days old: 40 - 181+ days old: 15 - missing date: 0 - future date: 50 and flagged as `stale_record` Value score: - null: 35 - under $5,000: 25 - $5,000-$24,999.99: 50 - $25,000-$99,999.99: 75 - $100,000-$500,000: 90 - over $500,000: 100 Trade fit score: - exact category keyword in permit type: 100 - exact category keyword in description: 85 - related keyword signal in description: 65 - generic construction/remodel signal: 45 - no match: 10 Completeness score: - +20 permit ID - +20 issued date - +20 address - +15 description - +15 permit type or status - +10 contractor/applicant/company ### Lead Grades | grade | score range | |---|---| | A | 80-100 | | B | 65-79.999 | | C | 45-64.999 | | D | 0-44.999 | Grades are opportunity-signal grades, not buyer-intent guarantees. ### Source Health Each selected source reports: - `status`: `healthy`, `empty`, `degraded`, or `failed` - `recordsFetched` - `recordsReturned` - `latestIssuedDate` - `warnings` - `errors` Status meanings: - `healthy`: fetch and pipeline succeeded, or the source produced a valid result. - `empty`: fetch succeeded but no records matched. - `degraded`: partial failure, malformed rows skipped, or warnings crossed a threshold. - `failed`: source fetch failed completely or all fetched rows failed normalization. Warnings use stable codes such as: - `source_returned_zero_rows` - `source_fetch_failed` - `records_skipped_missing_date` - `records_skipped_min_estimated_value` - `malformed_records_skipped` - `includeAiScoring_requested_disabled_mvp` - `source_latest_date_stale` - `maxResultsPerCity_capped_results` ### Limitations - Coverage is limited to five supported public datasets. - Public data can lag, change schema, or include incomplete fields. - Some sources do not provide contractor fields. - Some contacts may be applicants, owners, or permit representatives, not sales contacts. - Estimated values may be missing, rounded, entered inconsistently, or source-specific. - Trade matching is deterministic keyword matching, not legal or professional classification. - Source URLs are not available for every dataset. ### Ethical / Public-Data Boundaries Use this Actor for lawful public-data analysis, market research, and operational planning. Do not use it for spam, harassment, deceptive outreach, unlawful profiling, or automated contact enrichment. If you use public permit data for sales research, you are responsible for compliance with applicable laws, platform rules, and local norms. ### Troubleshooting | issue | likely cause | what to check | |---|---|---| | No records returned | Date/value/grade filters too narrow | Lower `minEstimatedValue`, widen dates, include more grades | | Source is `empty` | Fetch worked but filters matched nothing | Check `issuedAfter`, `issuedBefore`, and source health | | Source is `degraded` | Partial failure or malformed rows | Inspect `sourceHealth[city].warnings` | | Source is `failed` | Endpoint failure or all rows failed normalization | Inspect `sourceHealth[city].errors` | | `includeAiScoring` warning | AI scoring is disabled in MVP | Leave `includeAiScoring` as false | | Missing contractor fields | Source may not provide reliable contractor data | Treat output as permit intelligence, not verified leads | ### Local Development / Test Commands Run the unit test suite: ```bash .venv/bin/pytest -q -s actors/permit-signal-scout/test/test_schema.py actors/permit-signal-scout/test/test_socrata_client.py actors/permit-signal-scout/test/test_source_adapters.py actors/permit-signal-scout/test/test_filters_dedupe.py actors/permit-signal-scout/test/test_scoring.py actors/permit-signal-scout/test/test_main_pipeline.py actors/permit-signal-scout/test/test_source_health.py actors/permit-signal-scout/test/test_examples.py actors/permit-signal-scout/test/test_local_actor_packaging.py ``` Run a tiny read-only endpoint smoke test: ```bash .venv/bin/python actors/permit-signal-scout/scripts/smoke_fetch_limit1.py ``` Run a small read-only local sample: ```bash .venv/bin/python actors/permit-signal-scout/scripts/run_local_sample.py ``` Run launch readiness: ```bash .venv/bin/python actors/permit-signal-scout/scripts/launch_readiness_check.py ``` Run local Actor-style storage output without publishing: ```bash .venv/bin/python actors/permit-signal-scout/scripts/run_actor_local.py --input actors/permit-signal-scout/examples/input_local_smoke.json --storage-dir actors/permit-signal-scout/.local-storage ``` This writes records to `datasets/default/*.json` and the run summary to `key_value_stores/default/RUN_SUMMARY.json` under the selected storage directory. ### Launch Readiness The launch readiness check fetches a small sample from the five supported public Socrata sources, runs the full local pipeline, prints source health, prints the top five records, and returns a verdict: - `PASS`: all selected sources are healthy or empty with no critical errors. - `WARN`: one or more sources degraded/failed but the pipeline still returned records. - `FAIL`: all sources failed or no useful pipeline result could be produced. ### Next Step PS-011 adds local Apify-compatible packaging. The next step is a private Apify test run after explicitly confirming the packaging and local storage output. # Actor input Schema ## `cities` (type: `array`): Official public permit sources to query. ## `issuedAfter` (type: `string`): Return permits issued on or after this ISO date. Runtime default is today minus 30 days. ## `issuedBefore` (type: `string`): Optional ISO date upper bound for issued date filtering. ## `tradeKeywords` (type: `array`): Trade terms to match later during classification/scoring. ## `minEstimatedValue` (type: `number`): Optional minimum estimated permit value. Records with missing value are retained for MVP unless filtering is applied by a later adapter. ## `maxResultsPerCity` (type: `integer`): Maximum normalized records to fetch per selected city. ## `includeAiScoring` (type: `boolean`): Reserved for a later version. MVP uses deterministic scoring only and should warn when this is true. ## `outputMode` (type: `string`): Output ordering/grouping mode. ## `includeRawRecord` (type: `boolean`): Include the original Socrata row on each normalized record. ## `sortBy` (type: `string`): Sort key for final records. ## `leadGradeFilter` (type: `array`): Lead grades to include after scoring is implemented. ## Actor input object example ```json { "cities": [ "austin_tx", "chicago_il", "nyc_ny", "cincinnati_oh", "san_francisco_ca" ], "tradeKeywords": [ "roofing", "hvac", "solar", "plumbing", "electrical", "remodeling", "adu", "multifamily", "commercial", "restoration", "general construction" ], "maxResultsPerCity": 500, "includeAiScoring": false, "outputMode": "ranked", "includeRawRecord": false, "sortBy": "leadQualityScore", "leadGradeFilter": [ "A", "B", "C", "D" ] } ``` # 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("careybrown/permit-signal-scout").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 = {} # Run the Actor and wait for it to finish run = client.actor("careybrown/permit-signal-scout").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 '{}' | apify call careybrown/permit-signal-scout --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=careybrown/permit-signal-scout", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Permit Signal Scout", "description": "Normalize and rank public permit records into construction opportunity signals.", "version": "0.1", "x-build-id": "M5bWNE72RIHfoFaf9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/careybrown~permit-signal-scout/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-careybrown-permit-signal-scout", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/careybrown~permit-signal-scout/runs": { "post": { "operationId": "runs-sync-careybrown-permit-signal-scout", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/careybrown~permit-signal-scout/run-sync": { "post": { "operationId": "run-sync-careybrown-permit-signal-scout", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "cities": { "title": "Cities", "type": "array", "description": "Official public permit sources to query.", "items": { "type": "string", "enum": [ "austin_tx", "chicago_il", "nyc_ny", "cincinnati_oh", "san_francisco_ca" ] }, "default": [ "austin_tx", "chicago_il", "nyc_ny", "cincinnati_oh", "san_francisco_ca" ] }, "issuedAfter": { "title": "Issued After", "type": "string", "description": "Return permits issued on or after this ISO date. Runtime default is today minus 30 days." }, "issuedBefore": { "title": "Issued Before", "type": "string", "description": "Optional ISO date upper bound for issued date filtering." }, "tradeKeywords": { "title": "Trade Keywords", "type": "array", "description": "Trade terms to match later during classification/scoring.", "items": { "type": "string" }, "default": [ "roofing", "hvac", "solar", "plumbing", "electrical", "remodeling", "adu", "multifamily", "commercial", "restoration", "general construction" ] }, "minEstimatedValue": { "title": "Minimum Estimated Value", "minimum": 0, "type": "number", "description": "Optional minimum estimated permit value. Records with missing value are retained for MVP unless filtering is applied by a later adapter." }, "maxResultsPerCity": { "title": "Maximum Results Per City", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum normalized records to fetch per selected city.", "default": 500 }, "includeAiScoring": { "title": "Include AI Scoring", "type": "boolean", "description": "Reserved for a later version. MVP uses deterministic scoring only and should warn when this is true.", "default": false }, "outputMode": { "title": "Output Mode", "enum": [ "ranked", "byCity", "rawNormalized" ], "type": "string", "description": "Output ordering/grouping mode.", "default": "ranked" }, "includeRawRecord": { "title": "Include Raw Record", "type": "boolean", "description": "Include the original Socrata row on each normalized record.", "default": false }, "sortBy": { "title": "Sort By", "enum": [ "leadQualityScore", "issuedDate", "estimatedValue", "sourceCity" ], "type": "string", "description": "Sort key for final records.", "default": "leadQualityScore" }, "leadGradeFilter": { "title": "Lead Grade Filter", "type": "array", "description": "Lead grades to include after scoring is implemented.", "items": { "type": "string", "enum": [ "A", "B", "C", "D" ] }, "default": [ "A", "B", "C", "D" ] } } }, "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 } } } } } } } } } } ```