RSS & Atom Feed Health Auditor

Publishers, podcasts and monitoring teams need deterministic checks for public RSS or Atom feeds, item counts, duplicate links and date metadata.

RSS & Atom Feed Health Auditor is a focused QuanMatrix Actor designed for teams that need repeatable evidence rather than screenshots, vague summaries, or manual spot checks. It accepts public HTTP/HTTPS targets, performs a narrowly scoped inspection, and writes structured records to the default Apify dataset. The product is intentionally specialized so that its runtime, permissions, pricing, and limitations remain easy to understand.

Why use this Actor

Many web-quality checks are simple in isolation but expensive when repeated manually across dozens or hundreds of targets. This Actor turns that recurring problem into a deterministic workflow. It can be used interactively, scheduled, connected to another Actor, or integrated into a QA pipeline. Results contain explicit status, score, issue codes, and product-specific evidence so downstream automation can decide what to do next without parsing prose.

The design favors low runtime cost and transparent behavior. It does not require an account on the target website, a paid third-party API, a browser session, or an external AI service. Network access is limited to public HTTP/HTTPS destinations and private, loopback, link-local, reserved, or otherwise unsafe targets are rejected.

Key features

• Supports common RSS and Atom structures in one lightweight audit.
• Reports item count, duplicate links and publication-date coverage.
• Uses structured XML parsing rather than browser screenshots or prose.
• Requires no feed-management account, paid API or external AI service.
• Produces one structured dataset record for every submitted target, including explicit failure records.
• Uses bounded downloads and conservative runtime settings to keep resource usage predictable.
• Works with Apify scheduling, API calls, Tasks, datasets, webhooks, and downstream automation.

Input

Provide a JSON object with a urls array containing up to 100 public targets.

{"urls":["https://example.com","https://www.python.org"]}

Only public HTTP and HTTPS destinations are supported. Inputs that resolve to private or local network ranges are rejected deliberately.

Output

Each target produces a dataset item with input, final url, ok, HTTP status, numeric score, an issues array, and additional evidence relevant to this Actor. Successful and failed targets remain visible, which makes batch processing easier to audit.

Example

{"input":"https://example.com","url":"https://example.com","ok":true,"status":200,"score":100,"issues":[]}

The exact evidence fields depend on the product-specific check, while the common fields remain stable for automation.

Use cases

• Publishers
• Podcast operations
• Content monitoring
• News intelligence
• Scheduled regression checks after deployments or content changes.
• Agency and consultancy audits that need reusable JSON evidence.
• Data pipelines that need a narrow quality gate before subsequent processing.

Pricing

Planned pricing is $0.0013 USD per qualified result. The price is tied to the result written to the dataset, not to hidden subscriptions or external API charges. QuanMatrix reviews pricing against runtime cost, adoption, competition, conversion, and observed margin. Keywords used for market tracking include: rss feed, atom feed, feed health, podcast rss.

Limitations

This Actor evaluates evidence visible through ordinary public HTTP, XML, JSON, or server-delivered HTML. It does not replace authenticated testing, full browser rendering, penetration testing, legal review, or platform-specific administrative tools. JavaScript-generated state may not be visible when the server response does not include it. Some websites intentionally block automated requests, rate-limit traffic, or vary content by geography and client characteristics. Those conditions are reported rather than silently discarded.

Privacy and permissions

The Actor uses limited permissions and does not request credentials. It does not intentionally access private networks, internal services, or local addresses. Submitted URLs and resulting evidence are processed through standard Apify storage according to the user's Apify configuration. No paid external AI model or third-party enrichment API is required.

Differentiation

This is not a generic scraper wearing a different title. Its scoring, issue codes, evidence fields, and test cases are built around one concrete recurring problem. That narrower scope reduces maintenance risk, improves interpretability, and makes the output easier to combine with automated actions.

Feed intelligence and regression gate

The Gen2 feed audit keeps RSS/Atom item, link and date checks and adds freshness SLA, date-coverage scoring, duplicate ID detection, feed fingerprints, previous-run comparison, regression detection and GO / WARN / BLOCK decisions for publishing automation.