javimosch/open-claw-skills/feed-diet
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Checking that the SKILL.md file is still in the repository.
Audit your information diet across HN and RSS feeds — beautiful reports with category breakdowns, ASCII charts, and personalized recommendations.
Install
npx vskill@latest install javimosch/open-claw-skills/feed-dietSKILL.md
🍽️ Feed Diet
Audit your information diet and get a gorgeous report showing what you actually consume.
Trigger
Activate when the user mentions any of:
- "feed diet"
- "information diet"
- "audit my feeds"
- "what am I reading"
- "analyze my HN"
- "reading habits"
- "content diet"
- "feed report"
Instructions
Audit Mode (default)
- Determine the data source. Ask the user for one of:
- A Hacker News username (e.g., "tosh")
- An OPML file path containing RSS feed subscriptions
- Fetch the content. Run the appropriate fetch script:
```bash # For HN: bash "$SKILL_DIR/scripts/hn-fetch.sh" USERNAME 100
# For OPML: bash "$SKILL_DIR/scripts/opml-parse.sh" /path/to/feeds.opml ```
- Classify items. Pipe the fetched items through the classifier:
``bash cat items.jsonl | bash "$SKILL_DIR/scripts/classify.sh" > classified.jsonl `` The classifier uses LLM (if ANTHROPIC_API_KEY or OPENAI_API_KEY is set) or falls back to keyword matching.
- Generate the report. Run the main entry point:
``bash bash "$SKILL_DIR/scripts/feed-diet.sh" audit --hn USERNAME --limit 100 ``
- Present the report to the user. The output is Markdown — render it directly.
Digest Mode (weekly curated reading)
When the user wants a filtered reading list based on their goals:
Quick Reference
| Command | Description | |
|---|---|---|
feed-diet audit --hn USER | Full diet audit for an HN user | |
feed-diet audit --opml FILE | Full diet audit from RSS feeds | |
feed-diet digest --hn USER --goal "X" | Weekly digest filtered by goals |
Notes for the Agent
- Be conversational. After presenting the report, offer observations like "Looks like you're heavy on news — want me to suggest some deeper technical feeds?"
- Suggest the digest mode if the user seems interested in filtering their reading.
- The report is the star. Don't summarize it — present it in full. It's designed to be screenshot-worthy.
- If classification seems off, mention that setting an LLM API key improves accuracy.
Discord v2 Delivery Mode (OpenClaw v2026.2.14+)
When the conversation is happening in a Discord channel:
- Send a compact first summary (top category, diversity score, top 2 recommendations), then ask if the user wants the full report.
- Keep the first response under ~1200 characters and avoid wide category tables in the first message.
- If Discord components are available, include quick actions:
Show Full Diet ReportGenerate Weekly DigestShow Recommendations- If components are not available, provide the same follow-ups as a numbered list.
- Prefer short follow-up chunks (<=15 lines per message) when sharing long reports.
References
scripts/feed-diet.sh— Main entry pointscripts/hn-fetch.sh— Hacker News story fetcherscripts/opml-parse.sh— OPML/RSS feed parserscripts/classify.sh— Batch content classifier (LLM + fallback)scripts/common.sh— Shared utilities and formatting
Examples
Example 1: HN Audit
User: "Audit my HN reading diet — my username is tosh"
Agent runs:
Output: A full Markdown report with category breakdown table, top categories with sample items, surprising finds, and recommendations.
Example 2: Weekly Digest
User: "Give me a digest of what's relevant to my work on compilers and programming languages"
Agent runs:
Output: A curated reading list of 10-20 items ranked by relevance to the user's goals.
Example 3: RSS Feed Audit
User: "Here's my OPML file, tell me what my feed diet looks like"
Agent runs:
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/tkuehnl/feed-diet/SKILL.md
Popularity
- 7-day trend score
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