# OSHA Violation Risk & Time-Series (`fried_calamaries/osha-violation-risk`) Actor Turn any US employer's OSHA inspection history into a risk score, repeat-offender flag, and violation time-series — severity-weighted, auditable, and tracked over time. - **URL**: https://apify.com/fried\_calamaries/osha-violation-risk.md - **Developed by:** [ByteMe](https://apify.com/fried_calamaries) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.02 / employer risk report 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 ## OSHA Violation Risk & Time-Series ### Pain points - OSHA's IMIS database has 5M+ inspections and 13M+ violations, but no risk score — you read raw citations by hand. - Underwriters and due-diligence teams need a defensible safety-risk signal per employer, not a pile of citation rows. - Spotting repeat offenders and whether violations are trending up requires manually stitching years of inspections together. ### What we solve - Pull every OSHA inspection for an employer and its citations (gravity, penalties, standards, dates). - Compute a deterministic, auditable 0-100 risk score weighted by violation severity and recency. - Flag repeat offenders, chart violations over time, and label the trend (rising / flat / falling). - Run on a schedule to catch new inspections, new violations, and risk-score changes. ### Summary Give it a US employer name and get back an **OSHA safety-risk report**: every inspection and citation (gravity, penalty, standard, dates) rolled up into a **deterministic, auditable risk score** (0-100, severity-weighted and recency-decayed), a **repeat-offender** flag, total penalties, and a **violations-over-time** series with a rising/flat/falling trend. Built on OSHA's public IMIS data — no scraping fragility, no anti-bot. Run it on a schedule and it also reports **what changed** since last time: new inspections, new violations, and risk-score movement. Built for safety consultants, insurance underwriters, and supply-chain due-diligence. ### Who it's for - Insurance underwriters pricing workers'-comp and liability risk - Safety consultants and EHS teams benchmarking employers - Supply-chain and vendor due-diligence teams - Investors and M&A diligence screening for safety liabilities ### How to use Set the input, run the actor, and collect results from the run's dataset (export to JSON/CSV/Excel, or pull via the Apify API). Example input: ```json { "employers": [ "Dollar General" ], "maxInspectionsPerEmployer": 25, "compareToPrevious": true } ```` See **Inputs** below for every available field. ### What you get One row per record: | Field | Description | |---|---| | `query` | The employer name you searched | | `risk_score` | Deterministic 0-100 severity-weighted, recency-decayed risk score | | `risk_band` | low / medium / high | | `repeat_offender` | True if any Repeat-gravity violations | | `trend` | rising / flat / falling (recent vs prior 2-year windows) | | `by_gravity` | Violation counts by OSHA gravity (willful/repeat/serious/other) | | `total_current_penalty` | Sum of current penalties (USD) | | `violation_time_series` | Violations + penalty per year | | `inspection_count / violation_count` | Totals analyzed | | `inspections` | Per-inspection detail including each citation | | `new_inspections / new_violations / risk_score_delta` | What changed since the previous run (monitoring) | | `source_url` | The OSHA search this report came from | Sample: ```json { "query": "Dollar General", "state": null, "establishments": [ "Dollar General Store 12345" ], "inspection_count": 2, "violation_count": 2, "by_gravity": { "serious": 2 }, "total_current_penalty": 14000, "total_initial_penalty": 14000, "risk_score": 21, "risk_band": "medium", "repeat_offender": false, "trend": "falling", "violation_time_series": [ { "year": 2024, "violations": 2, "penalty": 14000 } ], "first_seen": false, "new_inspections": 0, "new_violations": 0, "risk_score_delta": 0, "source_url": "https://www.osha.gov/ords/imis/establishment.search?establishment=Dollar+General&state=all" } ``` ### Inputs | Field | Required | Type | Default | Description | |---|---|---|---|---| | `employers` | yes | array | `["Dollar General"]` | US employer / company names to analyze (e.g. 'Dollar General'). One risk report per name, aggregating all of that employer's OSHA inspections. | | `state` | no | string | — | Optional two-letter state code (e.g. 'TX') to limit inspections to that state. Leave empty for nationwide. | | `maxInspectionsPerEmployer` | no | integer | `25` | Cap on inspections pulled per employer (most-recent first). Each inspection is one detail fetch; higher = more complete history, slower run. | | `compareToPrevious` | no | boolean | `true` | When on (default), diff each employer against the previous run and report what changed — new inspections, new violations, risk-score delta. Run on a schedule to track employers over time. | | `proxyConfiguration` | no | object | `{"useApifyProxy": false}` | Optional. OSHA's public site is reachable directly; a proxy is rarely needed. | ### Pricing (Pay Per Event) You pay per result (`dataset-item`) — **no charge for empty runs**. Example: **100 employer risk reports** at *$0.02/result* ≈ **$2.00**. One charge per employer risk report produced. Employers with no OSHA inspections found are returned empty and not charged. Apify platform usage (compute) is billed separately per your plan. ### Use cases - Underwriting risk signal — get a defensible, auditable safety-risk score per employer. - Vendor due diligence — screen suppliers for repeat OSHA violations before contracting. - Safety benchmarking — compare employers' violation history and penalty totals. - Monitoring — run weekly to catch new inspections and rising risk on watched employers. ### Why this actor - A risk score, not raw citations — severity-weighted, recency-decayed, and fully auditable (the formula is documented). - Repeat-offender flag, penalty totals, and a violations-over-time trend in one report. - Built on OSHA's public data — no anti-bot fragility — and tracks what changes over time. ### Limitations & updates Covers OSHA federal and state-plan inspection data exposed in the public IMIS establishment search. Establishment names in OSHA data are per-inspection and inconsistent, so reports aggregate at the employer-query level (use the state filter to narrow). The risk score reflects recorded violations only — not unreported hazards — and is a relative signal, not a regulatory determination. ### FAQ **Where does the data come from?** OSHA's public IMIS enforcement database (inspections + citations). Public data, no login required. **How is the risk score calculated?** A deterministic formula: violations weighted by OSHA gravity (Willful > Repeat > Serious > Other) and decayed by recency, scaled to 0-100. It's reproducible and auditable — the same history always yields the same score. **What counts as a repeat offender?** Any employer with one or more citations OSHA classified as 'Repeat' gravity. **Can I limit to one state?** Yes — pass a two-letter state code to restrict the inspections analyzed; leave it empty for nationwide. **How am I charged?** Per employer risk report produced. Employers with no inspections found are returned empty and not charged. **Can it track changes over time?** Yes — run on a schedule and it reports new inspections, new violations, and risk-score movement since the previous run. # Actor input Schema ## `employers` (type: `array`): US employer / company names to analyze (e.g. 'Dollar General'). One risk report per name, aggregating all of that employer's OSHA inspections. ## `state` (type: `string`): Optional two-letter state code (e.g. 'TX') to limit inspections to that state. Leave empty for nationwide. ## `maxInspectionsPerEmployer` (type: `integer`): Cap on inspections pulled per employer (most-recent first). Each inspection is one detail fetch; higher = more complete history, slower run. ## `compareToPrevious` (type: `boolean`): When on (default), diff each employer against the previous run and report what changed — new inspections, new violations, risk-score delta. Run on a schedule to track employers over time. ## `proxyConfiguration` (type: `object`): Optional. OSHA's public site is reachable directly; a proxy is rarely needed. ## Actor input object example ```json { "employers": [ "Dollar General", "Dollar Tree" ], "maxInspectionsPerEmployer": 25, "compareToPrevious": true, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `reports` (type: `string`): Per-employer OSHA risk report: risk score/band, repeat-offender flag, trend, penalties, and violations over time. # 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 = { "employers": [ "Dollar General" ] }; // Run the Actor and wait for it to finish const run = await client.actor("fried_calamaries/osha-violation-risk").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 = { "employers": ["Dollar General"] } # Run the Actor and wait for it to finish run = client.actor("fried_calamaries/osha-violation-risk").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 '{ "employers": [ "Dollar General" ] }' | apify call fried_calamaries/osha-violation-risk --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fried_calamaries/osha-violation-risk", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "OSHA Violation Risk & Time-Series", "description": "Turn any US employer's OSHA inspection history into a risk score, repeat-offender flag, and violation time-series — severity-weighted, auditable, and tracked over time.", "version": "0.1", "x-build-id": "B2vdd576Bq2ae9zs8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fried_calamaries~osha-violation-risk/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fried_calamaries-osha-violation-risk", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fried_calamaries~osha-violation-risk/runs": { "post": { "operationId": "runs-sync-fried_calamaries-osha-violation-risk", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fried_calamaries~osha-violation-risk/run-sync": { "post": { "operationId": "run-sync-fried_calamaries-osha-violation-risk", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "employers" ], "properties": { "employers": { "title": "Employers", "type": "array", "description": "US employer / company names to analyze (e.g. 'Dollar General'). One risk report per name, aggregating all of that employer's OSHA inspections.", "items": { "type": "string" } }, "state": { "title": "State filter", "type": "string", "description": "Optional two-letter state code (e.g. 'TX') to limit inspections to that state. Leave empty for nationwide." }, "maxInspectionsPerEmployer": { "title": "Max inspections per employer", "minimum": 1, "maximum": 200, "type": "integer", "description": "Cap on inspections pulled per employer (most-recent first). Each inspection is one detail fetch; higher = more complete history, slower run.", "default": 25 }, "compareToPrevious": { "title": "Monitor changes", "type": "boolean", "description": "When on (default), diff each employer against the previous run and report what changed — new inspections, new violations, risk-score delta. Run on a schedule to track employers over time.", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional. OSHA's public site is reachable directly; a proxy is rarely needed.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```