# GitHub Activity Stream ā€” AI Agent Dev Monitoring API (`logiover/github-activity-stream`) Actor Keyless GitHub activity stream for AI agents: commits, pull requests, issues, releases and events for any repo, org or user. Time-windowed, paginated, thousands of events per run. Actors, additions, labels, states and URLs per row. No API key, no browser. - **URL**: https://apify.com/logiover/github-activity-stream.md - **Developed by:** [Logiover](https://apify.com/logiover) (community) - **Categories:** Developer tools, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Activity Stream ā€” AI Agent Dev Monitoring API > **Keyless GitHub activity stream for AI coding agents.** Pull commits, pull requests, issues, releases and public events for any repo, org or user. Time-windowed, paginated ā€” thousands of events per run. Each event becomes one structured row with actor, state, additions/deletions, labels and URL. No API key, no headless browser. Built for the new wave of **AI agents that reason about software development** ā€” coding agents that summarize "what changed in this repo this week", dependency-monitoring agents that detect security commits and releases, release-tracking agents that watch for new versions, and RAG pipelines that ground LLM answers in current dev activity instead of stale training-set snapshots. --- ### šŸŽÆ What this Actor is for GitHub is the heartbeat of open-source and most dev teams, but its activity is scattered across commits, PRs, issues, releases and events ā€” each a separate API endpoint with its own schema. When an AI agent is asked *"what did the React team ship this week?"* or *"any security commits in kubernetes/kubernetes lately?"*, it needs **structured, time-windowed, multi-type activity** ā€” not raw API JSON to re-parse. `github-activity-stream` is that dev-grounding layer: - **One repo ā†’ all activity.** Commits, PRs, issues and releases for a repo in one run, normalized to a common schema. Big repos yield thousands of events. - **Org-wide monitoring.** `org` mode lists an org's public repos (sorted by recent activity) and pulls activity from each ā€” monitor an entire ecosystem (kubernetes, vercel, facebook) in one run. - **User activity.** `user` mode pulls a user's public event feed (commits, PRs, reviews, pushes) ā€” 90 days of history. - **Time-windowed.** `since` filter keeps only events after a date ā€” ideal for daily/weekly delta runs. - **Triage-ready schema.** Every event carries `type` (commit/pull/issue/release), `repo`, `actor`, `title`, `state`, `createdAt`, `additions`/`deletions` (PRs), `labels`, `tagName`/`isPrerelease` (releases), and `url`. - **AI-agent friendly.** Predictable fields, ISO dates, nullable values. Drop straight into a prompt or a vector store. - **No keys, no browser.** Pure HTTP + JSON API on a small Node 20 container, with Apify proxy IP rotation to spread GitHub's keyless 60 req/hr/IP limit. Optional token raises to 5000/hr. --- ### āœØ Key features - **šŸ“¦ Commits** ā€” `/repos/{o}/{r}/commits?since=ā€¦` paginated. First-line message as `title`, author + date. - **šŸ”€ Pull requests** ā€” `/repos/{o}/{r}/pulls?state=all&sort=created` paginated + `since` filter. `additions`, `deletions`, `commits`, `merged`, `state`, `labels`. - **ā— Issues** ā€” `/repos/{o}/{r}/issues?state=all&since=ā€¦` (PRs filtered out ā€” they come from `/pulls`). `state`, `labels`. - **šŸ·ļø Releases** ā€” `/repos/{o}/{r}/releases` paginated. `tagName`, `isPrerelease`, `name`, publish date. - **šŸ‘¤ User events** ā€” `/users/{u}/events/public` (up to 10 pages, 90 days). Push/PR/issue/review events. - **šŸ¢ Org scan** ā€” `/orgs/{org}/repos?type=public&sort=updated` then per-repo activity. Cap with `maxOrgRepos`. - **šŸ“… Time window** ā€” `since` (ISO date) filters commits/issues/PRs to a delta window. - **šŸŒ Proxy IP rotation** ā€” Apify datacenter proxy rotates IPs per request to mitigate GitHub's keyless 60 req/hr/IP. Optional `ghToken` for 5000/hr. - **šŸ” Retry/backoff** ā€” 403 (rate-limit) and 5xx trigger exponential backoff retry (up to 6 attempts). - **šŸ’° Pay-per-result** ā€” charged per saved event, not per run. Empty results are free. --- ### šŸ¤– Why AI agents need this Dev activity is high-signal, high-frequency grounding for coding agents ā€” and tedious to collect. Each GitHub object type is a separate endpoint with pagination, rate limits and schema quirks. An agent that hits them directly reinvents merging and normalization every time, and burns the 60/hr keyless limit fast. `github-activity-stream` wraps it all into one reliable, proxy-rotated, pay-per-result Actor: 1. **Weekly dev summary agent.** A coding agent runs `repo` mode with `since: <7 days ago>` on a watched repo, summarizes the commits/PRs/releases, and posts a digest. 2. **Release tracker.** An agent watches `releases` for a dependency org (`kubernetes`, `vercel`), alerts on new versions, and drafts upgrade notes from the release bodies. 3. **Security-commit detector.** An agent scans recent commits for `security`, `cve`, `vuln`, `fix` keywords and flags them. 4. **Dependency health.** An agent pulls issues (open count, stale, label distribution) and PRs (merge velocity) to score a repo's maintenance health before adoption. 5. **Contributor monitoring.** An agent tracks a key maintainer's public events (`user` mode) to spot activity shifts. 6. **Org-wide radar.** An agent scans an entire org's repos (`org` mode) for recent activity to map where work is happening. 7. **RAG over dev activity.** Embed commit messages + PR titles into a vector store; answer "when did X get fixed?" with citations to the exact commit. Each of these is one Actor call (or a scheduled run). The output is a table of events ready for an LLM to summarize, filter, or alert on. --- ### šŸ“¦ What you get (output schema) Every run streams **one activity event per row** to the default dataset. A pull request row looks like: ```json { "repo": "microsoft/vscode", "type": "pull", "number": 210543, "title": "Fix terminal rendering on macOS", "action": null, "state": "closed", "actor": "user123", "createdAt": "2026-06-28T10:00:00Z", "updatedAt": "2026-07-01T15:00:00Z", "additions": 142, "deletions": 38, "commits": 3, "labels": ["bug", "terminal"], "merged": true, "isPrerelease": null, "tagName": null, "url": "https://github.com/microsoft/vscode/pull/210543", "scrapedAt": "2026-07-02T12:00:00.000Z" } ```` A release row carries `type: "release"`, `tagName: "1.21.0"`, `isPrerelease: false`. A commit row carries `type: "commit"`, the first-line message as `title`. A user event carries the event `type` (PushEvent, PullRequestEvent, ā€¦). Use the **Overview** view to scan all events, or the **By type** view to pivot on commit/PR/issue/release. *** ### šŸš€ How to use #### 1. Single repo weekly activity ```json { "mode": "repo", "repos": ["microsoft/vscode"], "eventTypes": ["commits", "pulls", "issues", "releases"], "since": "2026-06-25", "maxPerType": 200 } ``` #### 2. Org-wide scan (monitor an ecosystem) ```json { "mode": "org", "org": "kubernetes", "maxOrgRepos": 15, "eventTypes": ["pulls", "releases"], "since": "2026-06-01" } ``` #### 3. User public activity ```json { "mode": "user", "user": "torvalds", "maxPerType": 100 } ``` #### 4. Bulk: many repos ```json { "mode": "bulk", "repos": ["facebook/react", "vercel/next.js", "microsoft/typescript"], "since": "2026-06-01" } ``` #### From code (Apify SDK) ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('logiover/github-activity-stream').call({ mode: 'repo', repos: ['microsoft/vscode'], since: '2026-06-25', eventTypes: ['commits', 'releases'], }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); const releases = items.filter(i => i.type === 'release'); console.log(`${releases.length} releases this week`); ``` #### As an MCP tool for AI agents Wrap this Actor in an MCP server. A coding agent calls the tool with a repo + time window and receives normalized activity ā€” no GitHub API juggling, no rate-limit handling on the agent side. *** ### šŸ”§ Input fields | Field | Type | Default | Description | |---|---|---|---| | `mode` | enum | `repo` | `repo` (one repo), `org` (all org repos), `user` (user events), `bulk` (many repos). | | `repos` | array | ā€” | `owner/repo` slugs for `repo`/`bulk` modes. | | `org` | string | ā€” | Org slug for `org` mode. | | `user` | string | ā€” | Username for `user` mode. | | `eventTypes` | array | all | Which types: `commits`, `pulls`, `issues`, `releases`. | | `since` | string | ā€” | ISO date; only events after this. | | `maxPerType` | int | 200 | Cap per type per repo (1ā€“1000). | | `maxOrgRepos` | int | 20 | Cap on repos in `org` mode (1ā€“200). | | `ghToken` | string | ā€” | Optional GitHub token (60ā†’5000 req/hr). | | `useApifyProxy` | bool | true | Route through Apify datacenter proxy (IP rotation). | *** ### šŸ§© How it works 1. **Resolve targets.** `repo`/`bulk` use the `repos` list. `org` lists public repos (`/orgs/{org}/repos?type=public&sort=updated`), capped at `maxOrgRepos`. `user` targets the user event feed. 2. **Fetch per type.** For each repo, fetch the enabled types concurrently-ish (sequentially per type, paginated): commits (`/commits?since=ā€¦`), PRs (`/pulls?state=all&sort=created` + client-side `since` filter), issues (`/issues?state=all&since=ā€¦`, PRs filtered), releases (`/releases`). 3. **IP rotation.** Each request goes through the Apify datacenter proxy (rotating source IP) to mitigate GitHub's keyless 60 req/hr/IP. A `ghToken` (if provided) raises the limit to 5000/hr and is sent as `Authorization: Bearer`. 4. **Retry/backoff.** 403 (rate-limit) and 5xx trigger exponential backoff (up to 6 attempts). 404 (deleted/private repo) is treated as graceful empty. 5. **Normalize.** Each object is mapped to a common record: `type`, `repo`, `number`, `title`, `actor`, `createdAt`, `updatedAt`, `state`, `additions`/`deletions`/`commits` (PRs), `labels`, `merged` (PRs), `tagName`/`isPrerelease` (releases), `url`. 6. **Stream.** Each event is pushed to the dataset and one `result` event is charged. *** ### šŸ’” Tips & best practices - **Use `since` for deltas.** Without it, you pull full history (capped by `maxPerType`). For monitoring, always set `since` to the last run time. - **Schedule weekly repo runs.** `since: <7 days ago>` each week for a digest. Big repos (linux, vscode) yield hundreds of events. - **`org` mode for ecosystems.** Monitoring `kubernetes` or `vercel`? `org` mode + `maxOrgRepos: 15` + `eventTypes: ["pulls","releases"]` gives you the org's recent output in one run. - **Trim types for speed.** If you only need releases, set `eventTypes: ["releases"]`. Commits are the highest-volume (and slowest) type. - **Provide a `ghToken` for heavy use.** Keyless (60/hr/IP) is fine for monitoring a few repos via proxy rotation; for org-wide scans or frequent runs, a token (5000/hr) is much faster. - **Detect security commits.** Filter commit/PR `title` for `security|cve|vuln|fix|patch` to surface security work; pair with `cve-security-advisory-monitor`. - **Combine with related Actors.** Pair with `cve-security-advisory-monitor` (vuln DB), `certificate-transparency-monitor` (infra), and `docs-knowledge-base-scraper` (chunk the repo's docs). *** ### ā“ FAQ #### Does this Actor need any API keys? No. GitHub's API is keyless (60 req/hr/IP). The Apify proxy rotates IPs per request to effectively remove that cap. For heavy use, provide a `ghToken` (free Personal Access Token) to raise to 5000/hr. #### Why doesn't it fetch commit additions/deletions? The `/commits` list endpoint doesn't return per-commit stats (only the detail endpoint does). Fetching each commit's detail would multiply requests heavily. PR rows do carry `additions`/`deletions`/`commits` from the PR object. For per-commit stats, post-process by fetching specific commit URLs. #### How far back can I go? Commits/issues/PRs: as far as the repo history goes (capped by `maxPerType`). User events: GitHub keeps only 90 days of public events (10 pages max). Releases: all of them. #### Does it work for private repos? No. It uses public endpoints without auth (or with a token's public scope). For private repos, the token would need `repo` scope ā€” but this Actor targets public monitoring. #### Why are some PRs/commits missing the actor? GitHub anonymizes some commits (noreply emails) or the author has no GitHub account. `actor` is null in those cases. #### How is this priced? Pay-per-result: one `result` event per saved activity row. Runs that yield zero events (empty/deleted repo) are free. #### Will I get rate-limited? Keyless is 60 req/hr/IP. Proxy rotation spreads this; a `ghToken` removes the concern. 403s trigger backoff retry. #### Can AI agents call this directly? Yes. Expose it through an MCP server or Apify tool integration; the agent passes a repo + time window and gets normalized activity back. This is the primary design target. *** ### šŸ”— Related Actors - **cve-security-advisory-monitor** ā€” vulnerability DB (NVD/GHSA/OSV) for security context. - **certificate-transparency-monitor** ā€” new TLS certs (infra/attack-surface). - **github-repository-scraper** ā€” repo metadata search (complementary, search-focused). - **npm-package-intelligence-scraper** ā€” npm package metadata. - **docs-knowledge-base-scraper** ā€” chunk a repo's docs site for RAG. *** ### šŸ“ Changelog #### 2026-07-02 ā€” v1.0 - Initial release. - 4 modes: `repo`, `org`, `user`, `bulk`. - 4 event types: commits, pulls, issues, releases (+ user public events). - `since` time window, pagination, `maxPerType`/`maxOrgRepos` caps. - Optional `ghToken` (60ā†’5000 req/hr). - Apify datacenter proxy default (IP rotation). - Pay-per-result (`result` event per saved event). *** ### āš–ļø Disclaimer This Actor queries the public GitHub REST API (keyless or with a user-supplied token). Activity data is owned by the respective repository owners and contributors; respect GitHub's Terms of Service and rate limits. Use for dev monitoring, dependency tracking and AI-agent grounding on data that is already public. # Actor input Schema ## `mode` (type: `string`): What to monitor. ā€¢ **repo** ā€” activity for one repo (commits + PRs + issues + releases) (highest volume per target) ā€¢ **org** ā€” all public repos of an org, each with activity ā€¢ **user** ā€” a user's public events + their repos ā€¢ **bulk** ā€” many repos/orgs in one run ## `repos` (type: `array`): Array of `owner/repo` slugs for **repo** or **bulk** mode, e.g. `microsoft/vscode`, `facebook/react`. ## `org` (type: `string`): GitHub organization slug for **org** mode, e.g. `kubernetes`, `vercel`. ## `user` (type: `string`): GitHub username for **user** mode, e.g. `torvalds`. ## `eventTypes` (type: `array`): Which activity types to collect. Defaults to all. Fewer = faster. ## `since` (type: `string`): Only events after this date (YYYY-MM-DD or full ISO). Leave empty for all history (capped by maxResults). ## `maxPerType` (type: `integer`): Cap per event type per repo (commits, PRs, issues, releases each). ## `maxOrgRepos` (type: `integer`): Cap on repos to scan in org mode. ## `ghToken` (type: `string`): Optional GitHub Personal Access Token (raises rate limit from 60 to 5000 req/hr). Leave empty for keyless (proxy rotation spreads the 60/hr/IP limit). ## `useApifyProxy` (type: `boolean`): Route through Apify datacenter proxy (IP rotation). GitHub keyless is 60 req/hr/IP; rotation effectively removes the cap. ## Actor input object example ```json { "mode": "repo", "repos": [ "microsoft/vscode" ], "org": "kubernetes", "user": "torvalds", "eventTypes": [ "commits", "pulls", "issues", "releases" ], "since": "2026-06-01", "maxPerType": 100, "maxOrgRepos": 10, "ghToken": "", "useApifyProxy": true } ``` # Actor output Schema ## `results` (type: `string`): Full dataset of normalized GitHub activity events. # 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 = { "mode": "repo", "repos": [ "microsoft/vscode" ], "org": "kubernetes", "user": "torvalds", "eventTypes": [ "commits", "pulls", "issues", "releases" ], "since": "", "maxPerType": 100, "maxOrgRepos": 10, "useApifyProxy": true }; // Run the Actor and wait for it to finish const run = await client.actor("logiover/github-activity-stream").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`šŸ’¾ 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); }); // šŸ“š Want to learn more šŸ“–? Go to ā†’ 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 = { "mode": "repo", "repos": ["microsoft/vscode"], "org": "kubernetes", "user": "torvalds", "eventTypes": [ "commits", "pulls", "issues", "releases", ], "since": "", "maxPerType": 100, "maxOrgRepos": 10, "useApifyProxy": True, } # Run the Actor and wait for it to finish run = client.actor("logiover/github-activity-stream").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("šŸ’¾ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # šŸ“š Want to learn more šŸ“–? Go to ā†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "mode": "repo", "repos": [ "microsoft/vscode" ], "org": "kubernetes", "user": "torvalds", "eventTypes": [ "commits", "pulls", "issues", "releases" ], "since": "", "maxPerType": 100, "maxOrgRepos": 10, "useApifyProxy": true }' | apify call logiover/github-activity-stream --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=logiover/github-activity-stream", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Activity Stream ā€” AI Agent Dev Monitoring API", "description": "Keyless GitHub activity stream for AI agents: commits, pull requests, issues, releases and events for any repo, org or user. Time-windowed, paginated, thousands of events per run. Actors, additions, labels, states and URLs per row. No API key, no browser.", "version": "1.0", "x-build-id": "Vh358gMVT6VbSUXKF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/logiover~github-activity-stream/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-logiover-github-activity-stream", "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/logiover~github-activity-stream/runs": { "post": { "operationId": "runs-sync-logiover-github-activity-stream", "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/logiover~github-activity-stream/run-sync": { "post": { "operationId": "run-sync-logiover-github-activity-stream", "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": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "repo", "org", "user", "bulk" ], "type": "string", "description": "What to monitor.\n\nā€¢ **repo** ā€” activity for one repo (commits + PRs + issues + releases) (highest volume per target)\nā€¢ **org** ā€” all public repos of an org, each with activity\nā€¢ **user** ā€” a user's public events + their repos\nā€¢ **bulk** ā€” many repos/orgs in one run", "default": "repo" }, "repos": { "title": "Repos (repo & bulk mode)", "type": "array", "description": "Array of `owner/repo` slugs for **repo** or **bulk** mode, e.g. `microsoft/vscode`, `facebook/react`.", "items": { "type": "string" }, "default": [] }, "org": { "title": "Org (org mode)", "type": "string", "description": "GitHub organization slug for **org** mode, e.g. `kubernetes`, `vercel`." }, "user": { "title": "User (user mode)", "type": "string", "description": "GitHub username for **user** mode, e.g. `torvalds`." }, "eventTypes": { "title": "Event types", "type": "array", "description": "Which activity types to collect. Defaults to all. Fewer = faster.", "items": { "type": "string" }, "default": [ "commits", "pulls", "issues", "releases" ] }, "since": { "title": "Since (ISO date)", "type": "string", "description": "Only events after this date (YYYY-MM-DD or full ISO). Leave empty for all history (capped by maxResults)." }, "maxPerType": { "title": "Max events per type", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Cap per event type per repo (commits, PRs, issues, releases each).", "default": 200 }, "maxOrgRepos": { "title": "Max org repos (org mode)", "minimum": 1, "maximum": 200, "type": "integer", "description": "Cap on repos to scan in org mode.", "default": 20 }, "ghToken": { "title": "GitHub token (optional)", "type": "string", "description": "Optional GitHub Personal Access Token (raises rate limit from 60 to 5000 req/hr). Leave empty for keyless (proxy rotation spreads the 60/hr/IP limit).", "default": "" }, "useApifyProxy": { "title": "Use Apify datacenter proxy", "type": "boolean", "description": "Route through Apify datacenter proxy (IP rotation). GitHub keyless is 60 req/hr/IP; rotation effectively removes the cap.", "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 } } } } } } } } } } ```