System AtomCrafts

FeedCraft comes with a set of built-in “AtomCrafts” that perform specific processing steps on your feeds. You can chain these AtomCrafts together in a FlowCraft to create powerful pipelines.

Content Acquisition & Repair

These atoms help you fetch full content or fix common feed issues.

fulltext

Extracts the full content of the article from the original webpage.

• Use case: When the RSS feed only provides a summary or snippet.
• Mechanism: Uses a standard HTTP client to fetch the page and an algorithm to extract the main content. Fast and lightweight.

fulltext-plus

Extracts full content using a headless browser (Puppeteer).

• Use case: For websites that require JavaScript to render content or have strong anti-bot protections.
• Mechanism: Connects to the configured Browserless/Puppeteer service to render the page. Slower but more robust.
• Parameters:
  • mode (default: networkidle2): Wait condition.
    • load: Wait for the load event.
    • domcontentloaded: Wait for the DOMContentLoaded event.
    • networkidle0: Wait until there are 0 active network connections for at least 500ms.
    • networkidle2: Wait until there are no more than 2 active network connections for at least 500ms. (Recommended for SPAs).
  • wait (default: 0): Explicit wait time in seconds (e.g., 5).

proxy

Simple proxy for the feed.

• Use case: When you just want to forward the original feed without modification, or use FeedCraft as a central gateway.

guid-fix

Replaces the RSS item GUID with an MD5 hash of the item’s content.

• Use case: Some feeds change their GUIDs frequently even when content hasn’t changed, causing duplicate unread items in readers. This atom stabilizes the GUID based on content.

relative-link-fix

Converts relative links (e.g., <a href="/about">) in the content to absolute links (e.g., <a href="https://example.com/about">).

• Use case: Essential when extracting full content, as relative links will break when viewed in an RSS reader.

cleanup

Cleans up the HTML content to remove clutter.

• Use case: Improving readability by removing classes, styles, and empty tags.

---

Filtering

Control which items make it into your final feed.

limit

Limits the number of items in the feed.

• Parameters:
  • num (default: 10): The maximum number of items to keep.

time-limit

Filters out items that are older than a specific number of days.

• Parameters:
  • days (default: 7): Max age of articles in days.

keyword

Filters items based on keywords in the title or content.

• Parameters:
  • keywords: A comma-separated list of keywords to match (substring match, case-sensitive). Example: ad,sell,SALE.
  • mode: include (default) to keep matching items, or exclude to remove them.
  • scope: title, content, or all (default).

---

AI Enhancement

Use Large Language Models (LLM) to transform and enrich your content.

Note

These atoms require LLM configuration (API Key, Base URL, etc.) in your environment variables.

translate-title

Translates the article title to your target language.

• Parameters:
  • prompt: Custom prompt. Defaults to a standard translation prompt. Supports {{.TargetLang}} placeholder.

translate-content

Translates the entire article content, replacing the original.

• Parameters:
  • prompt: Custom prompt. Supports {{.TargetLang}}.

translate-content-immersive

Bilingual translation. Appends the translation after each paragraph of the original text.

• Parameters:
  • prompt: Custom prompt.

summary

Generates a summary of the article and prepends it to the content.

• Parameters:
  • prompt: Custom prompt for summarization.

introduction

Generates a short introduction or “lead-in” for the article.

• Parameters:
  • prompt: Custom prompt.

beautify-content

Re-formats the article using LLM to fix layout, remove ads, and standardizing Markdown, then converts back to clean HTML.

• Parameters:
  • prompt: Instructions for the “editor” persona.

---

AI Filtering

Advanced filtering using semantic understanding.

ignore-advertorial

Uses LLM to detect if an article is an advertorial or soft advertisement (evaluating both title and content) and removes it.

• Parameters:
  • prompt-for-exclude: A prompt that should return true if the item is an ad.

llm-filter

Generic LLM-based filter. You define the condition for exclusion. The LLM evaluates both the article title and content against this condition.

• Parameters:
  • filter_condition: A natural language question/condition. If the LLM answers “yes” (true), the item is removed.
  • Example: “Is this article about sports?” (Removes sports articles).