Discourse
- 75 installs
- 325 repo stars
- Updated August 2, 2026
- athola/claude-night-market
Discourse is an agent skill that gathers practitioner experience reports from HN, Lobsters, Reddit, and tech blogs on a topic.
About
Discourse is a Night Market library skill that scans Hacker News, Lobsters, Reddit, and selected tech blogs for real-world opinions and war stories about a technology or approach. Solo builders invoke it when spreadsheets of stars and docs are not enough—they need how practitioners actually felt after shipping, migrating, or regretting a choice. The workflow standardizes per-channel query construction, API or search execution, parsing into Finding objects, and merging results with clear attribution. It is deliberately narrow compared to paper search or code search, which keeps agent runs fast and on-topic. Use it during idea exploration, validation spikes, and build-phase integration picks when community sentiment should inform risk. It assumes network access and respectful API usage rather than bulk scraping without limits.
- Four channels: Hacker News (Algolia API), Lobsters (site search), Reddit (JSON API), curated tech blogs via WebSearch
- Workflow: build queries with tome.channels.discourse.*, fetch via WebFetch/WebSearch, merge into attributed Finding obje
- Explicit exclusions: not for academic papers (/tome:papers) or code examples (/tome:code-search)
- Library-role skill (~200 estimated tokens) with standard model hint for lightweight scans
- Cross-source merge preserves source attribution for downstream synthesis
Discourse by the numbers
- 75 all-time installs (skills.sh)
- Ranked #5,460 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 75 |
|---|---|
| repo stars | ★ 325 |
| Security audit | 2 / 3 scanners passed |
| Last updated | August 2, 2026 |
| Repository | athola/claude-night-market ↗ |
What it does
Pull practitioner experience reports from HN, Lobsters, Reddit, and tech blogs before you commit to a stack or architecture.
Who is it for?
Early technology due diligence and gut-checking hype with threaded community reports before writing a spec or POC.
Skip if: Peer-reviewed literature reviews, licensed dataset studies, or finding copy-paste code snippets—use the dedicated Tome paper and code-search skills instead.
When should I use this skill?
Gathering community opinions on a technology or approach; finding experience reports from HN, Reddit, or Lobsters (alwaysApply: false).
What you get
You receive merged, source-attributed findings from multiple discourse channels ready to inform scope, prototype, or integration choices.
- Merged Finding objects with per-source attribution
- Channel-specific query URLs or search plans executed in one workflow
By the numbers
- 4 discourse channels: Hacker News, Lobsters, Reddit, tech blogs
- ~200 estimated tokens for the library skill definition
Files
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
sourcefield 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
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Qualitative community scanner—not an academic corpus or GitHub code indexer.
FAQ
Who is discourse for?
Developers using Claude Night Market / Tome who want structured community sentiment from HN, Reddit, Lobsters, and blogs in one pass.
When should I use discourse?
Use in Idea/research when picking a stack; in Validate/scope when stress-testing an approach; in Build/integrations when comparing third-party services practitioners complain about or praise.
Is discourse safe to install?
It performs outbound fetches and searches; review the Security Audits panel on this Prism page and respect rate limits on public APIs you call through your agent.