# AI System Prompts Collector - Public Sources (`unrivaled_fortress/ai-system-prompts-collector`) Actor

Collect publicly posted AI system prompts from GitHub: search trending repos, extract prompt files and README snippets. No API key needed.

- **URL**: https://apify.com/unrivaled\_fortress/ai-system-prompts-collector.md
- **Developed by:** [David An](https://apify.com/unrivaled_fortress) (community)
- **Categories:** AI, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## 🤖 AI System Prompts Collector — Public Sources

Discover and collect **publicly posted AI system prompts** from GitHub's trending repositories — no API key, no login, no proxy.

### 🚀 Quick Start

1. Click **Try for free** (or Run)
2. (Optional) Adjust search queries and max repos
3. Run — get a structured list of prompts with source repos, star counts, and URLs

**No input?** The Actor runs demo queries (`system prompts`, `system prompt`, `ai system prompt`) so you see results instantly.

### 📦 What you get per item

| Field | Description |
|---|---|
| `source` | Where the prompt was found (`README` or `file:<name>`) |
| `repo` | GitHub repository (e.g. `x1xhlol/system-prompts-and-models-of-ai-tools`) |
| `stars` | Star count (popularity signal) |
| `url` | Direct link to the source |
| `promptText` | Extracted prompt-like content (first ~1,500 chars) |
| `description` | Repo description |

Plus a run summary (queries used / repos scanned / items collected).

### 💡 Use cases

- **Prompt research** — study how popular AI tools structure their system prompts
- **Product intelligence** — track prompt engineering trends in public repos
- **LLM app builders** — collect proven prompt patterns for your own agents
- **Competitive analysis** — see which prompt styles the top open-source projects use

### ⚙️ Technical notes

- Uses the free public GitHub Search API (no token required)
- **Public-source only**: collects content already openly published on GitHub — nothing leaked, nothing private. Repos branded as "leaked prompts" are skipped by default (optional `includeLeaks` input to include them)
- Per-repo try/catch isolation: one failing repo never breaks the batch
- Rate-polite: 1s delay between repo requests to respect GitHub limits

*Inspired by the growing ecosystem of public system-prompt collections (system-prompts-and-models-of-ai-tools, get-shit-done, Fabric).*

# Actor input Schema

## `queries` (type: `array`):

GitHub search keywords for system prompt repos. Empty input runs demo queries.

## `maxRepos` (type: `integer`):

How many top-starred repos to scan per query.

## `includeLeaks` (type: `boolean`):

By default, repos branded as 'leaked prompts' are skipped to keep the collection public-source only. Enable to include them.

## Actor input object example

```json
{
  "queries": [
    "system prompts",
    "system prompt",
    "ai system prompt"
  ],
  "maxRepos": 5,
  "includeLeaks": 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        "system prompts",
        "system prompt",
        "ai system prompt"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("unrivaled_fortress/ai-system-prompts-collector").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "queries": [
        "system prompts",
        "system prompt",
        "ai system prompt",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("unrivaled_fortress/ai-system-prompts-collector").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 '{
  "queries": [
    "system prompts",
    "system prompt",
    "ai system prompt"
  ]
}' |
apify call unrivaled_fortress/ai-system-prompts-collector --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=unrivaled_fortress/ai-system-prompts-collector",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/LzGlNhzr9czVxfQe4/builds/ggqKcQl4q6CdwJJoO/openapi.json