Catch up on RSS feeds by auto-summarizing new articles.

Prerequisites

Requires feedparser :

pip install feedparser

Helper Script

Use scripts/rss_helper.py for fetching data:

List recent articles from a feed

python3 scripts/rss_helper.py feed URL [limit]

Get article content (fetches full page)

python3 scripts/rss_helper.py article URL

Workflow

Load configuration

• Read feed list from references/feeds.json

• Read last run timestamp from references/state.json

• If first run: go back ~3 months

• Otherwise: only articles since last run

For each enabled feed:

• Run: python3 scripts/rss_helper.py feed "FEED_URL" 20

• Filter to articles published since last run

• Deduplicate against existing notes: grep -rl "media: {article_url}" "my-vault/07 Knowledge Base/Capture/Articles/"

• If a note with that URL exists: skip (already processed, may be missing from state)

For each new article:

• If feed provides full content, use that

• Otherwise, run: python3 scripts/rss_helper.py article "ARTICLE_URL" to fetch full text

• Summarize the content into bullet points (3-8 based on length/density)

• Create article note with status: Summarized

• Extract discoveries (see below)

Create discovery notes:

• While summarizing, identify any products, services, frameworks, tools, libraries, or technologies mentioned that might be worth exploring

• Search my-vault to check if a note already exists for each discovery

• For new discoveries, create a note in my-vault/01 Inbox/

• Link the discovery note from the article's Related field

Update state

• Write current timestamp to references/state.json

• Report summary of what was processed

Tagging

IMPORTANT: Read my-vault/09 System/Tag Index.md before processing to verify valid tags.

Tags MUST come from the canonical list - do not invent new tags. Common valid tags for this skill:

• #ai

• LLMs, agents, prompting, AI tools

• #llm

• Large Language Models, model comparisons

• #dev-tools

• IDEs, Git tooling, developer productivity

• #python , #javascript , #typescript

• language-specific

• #devops , #api , #databases

• infrastructure topics

• #atlassian , #jira , #confluence

• Atlassian products

Each feed in references/feeds.json has a tags array specifying default tags. Use these for article notes. Format: tags: ["tag1", "tag2"]

For discovery notes, choose tags based on what the discovery is (e.g., a Python library gets #python , an AI tool gets #ai ).

Article Note Format

Create in: my-vault/07 Knowledge Base/Capture/Articles/[Feed Name]/[Title].md

Sanitize filenames: remove special characters, limit length to ~80 chars.

class: Article media: https://example.com/article-url publishDate: YYYY-MM-DD status: Summarized author: Author Name reviewFrequency: lastReviewedDate: review: aliases: tags: ["tag1", "tag2"] cssclasses: archived:

Related:

Summary

Capture the actual conclusions and insights - what would someone learn from reading this? Not topic labels or "this article discusses X" but the substance:

Good: "Multi-agent systems outperform single agents when context exceeds what fits in one prompt - Anthropic's research system with Opus 4 lead + Sonnet 4 subagents beat single-agent Opus 4 by 90.2%"

Bad: "Discusses multi-agent architectures and when to use them"

Aim for 4-8 substantive bullets that capture the key takeaways, conclusions, data points, and actionable insights.

Discoveries

• [[Product Name]] - brief context from article
• (or "None" if nothing noteworthy)

Why Read?

[One sentence on whether this seems worth actually reading in full]

Feed Config

Edit references/feeds.json :

{ "feeds": [ { "name": "Feed Display Name", "url": "https://example.com/feed", "folder": "Folder Name", "tags": ["tag1", "tag2"], "priority": "high", "enabled": true } ] }

Tags should be from the canonical list in my-vault/09 System/Tag Index.md .

Discovery Note Format

Create in: my-vault/01 Inbox/[Name].md

class: Note reviewFrequency: lastReviewedDate: review: aliases: tags: ["tag1", "tag2"] cssclasses: archived:

Up: Related: [[Article Title]]

What is it?

[One sentence description of the product/service/framework]

Why look into it?

[Brief note on why it seemed interesting from the article context]

Links

• [Official site or docs if mentioned]

What counts as a discovery:

• Products or services (SaaS tools, apps, platforms)

• Frameworks or libraries (programming, ML, etc.)

• Technologies or protocols

• Notable companies or projects

• Methodologies or techniques worth researching

Skip creating notes for:

• Well-known mainstream things (e.g., "Python", "AWS", "React")

• Generic concepts that don't warrant their own note

• Things already covered extensively in existing notes

Processing Tips

• Process one feed at a time and report progress

• For long articles, focus on main arguments/takeaways

• If article content can't be fetched, summarize from title/description

• Skip articles that already exist in my-vault

• Keep summaries concise - this is for deciding what to read, not replacing reading

• When extracting discoveries, be selective - only create notes for things genuinely worth exploring

• Deduplicate by URL - some articles may appear in multiple feeds

Path Handling

CRITICAL - Never escape spaces with backslashes:

• Use paths exactly as shown: my-vault/07 Knowledge Base/... (with literal spaces)

• The Write tool handles spaces correctly - backslash escaping creates literal
  characters in directory names

• When using Bash commands, wrap paths in double quotes: "my-vault/07 Knowledge Base/..."