# GitHub Repository Insights (`lovely_radiologist/github-repo-insights`) Actor Turn any GitHub repo URL or search query into a structured profile: stars, contributors, languages, dependencies, license, and a composite health score. Built for AI agents, VC diligence, and dev-tool comparison sites. - **URL**: https://apify.com/lovely\_radiologist/github-repo-insights.md - **Developed by:** [Vivek Gaur](https://apify.com/lovely_radiologist) (community) - **Categories:** Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.50 / 1,000 repository profiles 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 ## GitHub Repository Insights Turn any GitHub repo URL or search query into a structured profile: stars history, contributors, languages, dependency files, license, and a composite **health score** — no more reading READMEs manually. ### The Health Score (unique differentiator) Each repo gets a `/100` health score computed from: - **Commit recency** (0–40 pts): Was the repo pushed in the last 7 days? 90 days? - **Issue ratio** (0–30 pts): Open issues relative to stars — lower is healthier - **Contributor diversity** (0–30 pts): Number of unique contributors ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `repoUrls` | string[] | — | GitHub URLs or `owner/repo` strings | | `searchQuery` | string | — | GitHub search query (used if repoUrls is empty) | | `maxRepos` | integer | 10 | Max repos to process | | `includeReadme` | boolean | true | Include README summary | | `includeDependencies` | boolean | false | Fetch package.json / requirements.txt | | `includeContributors` | boolean | true | Fetch top 10 contributors | ### Output ```json { "fullName": "vercel/next.js", "stars": 127000, "forks": 26800, "openIssues": 2341, "primaryLanguage": "TypeScript", "languages": { "TypeScript": 8942312, "JavaScript": 521430 }, "license": "MIT", "lastCommitDate": "2026-07-11T12:00:00Z", "contributorsCount": 10, "topContributors": [{ "login": "timneutkens", "contributions": 3842, "url": "..." }], "topics": ["nextjs", "react", "vercel"], "readmeSummary": "The React Framework for the Web...", "healthScore": 94, "fetchedAt": "2026-07-11T17:00:00.000Z" } ```` ### Pricing (PPE) | Event | Price | |-------|-------| | `actor-start` | $0.01 | | `repo-profile` | $0.04 per repo | ### Related Actors - [GitHub Trending Radar](https://apify.com/TODO) — find repos worth profiling - [GitHub Org Scraper](https://apify.com/TODO) — profile an entire organization - [arXiv Paper Extractor](https://apify.com/TODO) — cross-reference repos from papers # Actor input Schema ## `repoUrls` (type: `array`): List of GitHub repo URLs or 'owner/repo' strings. E.g. https://github.com/facebook/react or facebook/react. ## `searchQuery` (type: `string`): GitHub repository search query (uses GitHub search API). Ignored if repoUrls is provided. ## `maxRepos` (type: `integer`): Maximum number of repositories to process. ## `includeReadme` (type: `boolean`): Fetch and summarize the README.md (first 500 chars of body text). ## `includeDependencies` (type: `boolean`): Fetch package.json / requirements.txt / pyproject.toml / Cargo.toml. ## `includeContributors` (type: `boolean`): Fetch the top 10 contributors list. ## Actor input object example ```json { "repoUrls": [ "https://github.com/vercel/next.js" ], "searchQuery": "topic:llm stars:>500", "maxRepos": 10, "includeReadme": true, "includeDependencies": false, "includeContributors": true } ``` # 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 = { "repoUrls": [ "https://github.com/vercel/next.js" ], "searchQuery": "topic:llm stars:>500" }; // Run the Actor and wait for it to finish const run = await client.actor("lovely_radiologist/github-repo-insights").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 = { "repoUrls": ["https://github.com/vercel/next.js"], "searchQuery": "topic:llm stars:>500", } # Run the Actor and wait for it to finish run = client.actor("lovely_radiologist/github-repo-insights").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 '{ "repoUrls": [ "https://github.com/vercel/next.js" ], "searchQuery": "topic:llm stars:>500" }' | apify call lovely_radiologist/github-repo-insights --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lovely_radiologist/github-repo-insights", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Repository Insights", "description": "Turn any GitHub repo URL or search query into a structured profile: stars, contributors, languages, dependencies, license, and a composite health score. Built for AI agents, VC diligence, and dev-tool comparison sites.", "version": "0.1", "x-build-id": "8TMV2wwt1vX3fTQJ6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lovely_radiologist~github-repo-insights/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lovely_radiologist-github-repo-insights", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lovely_radiologist~github-repo-insights/runs": { "post": { "operationId": "runs-sync-lovely_radiologist-github-repo-insights", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lovely_radiologist~github-repo-insights/run-sync": { "post": { "operationId": "run-sync-lovely_radiologist-github-repo-insights", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "repoUrls": { "title": "Repository URLs", "type": "array", "description": "List of GitHub repo URLs or 'owner/repo' strings. E.g. https://github.com/facebook/react or facebook/react.", "items": { "type": "string" } }, "searchQuery": { "title": "Search Query", "type": "string", "description": "GitHub repository search query (uses GitHub search API). Ignored if repoUrls is provided." }, "maxRepos": { "title": "Max Repos", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of repositories to process.", "default": 10 }, "includeReadme": { "title": "Include README Summary", "type": "boolean", "description": "Fetch and summarize the README.md (first 500 chars of body text).", "default": true }, "includeDependencies": { "title": "Include Dependency Files", "type": "boolean", "description": "Fetch package.json / requirements.txt / pyproject.toml / Cargo.toml.", "default": false }, "includeContributors": { "title": "Include Top Contributors", "type": "boolean", "description": "Fetch the top 10 contributors list.", "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 } } } } } } } } } } ```