discourse

name: discourse role: library description: Scans HN, Lobsters, Reddit, and tech blogs for community experience reports. Use when gathering practitioner opinions on a technology or approach. alwaysApply: false category: research tags: - hackernews - reddit - lobsters - blogs - discourse estimated_tokens: 200 model_hint: standard

Discourse Search

When To Use

• Gathering community opinions on a technology or approach
• Finding experience reports from HN, Reddit, or Lobsters

When NOT To Use

• Academic research (use /tome:papers)
• Code examples (use /tome:code-search)

Scan community channels for discussions on a topic.

Channels

• Hacker News: Algolia API at hn.algolia.com
• Lobsters: WebSearch with site:lobste.rs
• Reddit: JSON API (append .json to URLs)
• Tech blogs: WebSearch targeting curated domains

Workflow

1. Build search URLs/queries per channel using tome.channels.discourse.* functions
2. Execute via WebFetch (APIs) or WebSearch (fallback)
3. Parse responses into Finding objects
4. Merge across sources with source attribution

Exit Criteria

• At least two community channels (HN, Lobsters, Reddit, or tech blogs) queried per invocation
• HN results fetched via Algolia API at hn.algolia.com (WebFetch); WebSearch used as fallback if the API is unreachable
• Each Finding object includes a source field identifying which channel (HN, Lobsters, Reddit, or blog) it came from
• If all WebFetch and WebSearch calls fail for every channel, the failure is reported explicitly rather than returning fabricated or empty findings