# Release notes evidence for AI coding agents (`rare_sunset/release-notes-evidence`) Actor

Extract source-linked release-note passages for an AI agent checking a dependency upgrade.

- **URL**: https://apify.com/rare\_sunset/release-notes-evidence.md
- **Developed by:** [Abdulrahman Baidaq](https://apify.com/rare_sunset) (community)
- **Categories:** AI, Agents, Developer tools
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## 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

## Release notes evidence for AI coding agents

This Actor turns a small, explicit set of official release-note pages into source-linked evidence records. It is designed to be called by an AI coding agent through the Apify MCP server while the agent is checking a dependency upgrade.

Each record includes the source URL, heading path, detected version, exact excerpt, retrieval time, content hash, publication date when available, and warnings. The Actor does not claim that a passage is true merely because it was extracted; the agent still needs to interpret the source and present the link.

### What it deliberately does not do

- It is not a general web search engine.
- It does not crawl arbitrary authenticated pages.
- It does not use a vector database or an LLM inside the Actor.
- It does not assign an uncalibrated confidence score.
- It does not replace reading the linked source.

Only use official pages that you are permitted to fetch. Check robots.txt, terms, rate limits, and applicable law. This implementation expects server-rendered HTML; a JavaScript-only release page needs a separate browser-based Actor.

### Local tests

```powershell
python -m unittest discover -s tests -v
```

### Example input

```json
{
  "sources": [
    "https://vendor.example/releases/1.5"
  ],
  "question": "Which breaking changes affect the upgrade from 1.4 to 1.5?",
  "max_passages": 6,
  "max_chars_per_passage": 700
}
```

Deploy the Actor, then expose it to an AI client through the official Apify MCP server. The client can discover the input schema, call the Actor, read the dataset output, and use each `sourceUrl` as the citation target.

The article’s selected client is Codex. Apify documents Codex as a supported MCP client; the live transcript must still be captured by the author after deployment. `examples/sample-local-record.json` is local output only and is not a substitute for that transcript.

# Actor input Schema

## `sources` (type: `array`):

One to four public official changelog or release-note pages. Do not use arbitrary authenticated URLs.

## `question` (type: `string`):

For example: Which breaking changes affect the upgrade from 1.4 to 1.5, and what migration steps are documented?

## `max_passages` (type: `integer`):

Limit the records returned to the AI agent.

## `max_chars_per_passage` (type: `integer`):

Keep each source excerpt compact enough for an agent context window.

## Actor input object example

```json
{
  "max_passages": 6,
  "max_chars_per_passage": 700
}
```

# Actor output Schema

## `evidence` (type: `string`):

No description

## `request` (type: `string`):

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("rare_sunset/release-notes-evidence").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("rare_sunset/release-notes-evidence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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 rare_sunset/release-notes-evidence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,rare_sunset/release-notes-evidence"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Cxib8kqBjRuk1RXy3/builds/UgHjrfkgW5c8fd6WH/openapi.json