blog-discourse
Research what people are actually saying about a topic in the last 30 days across Reddit, X / Twitter, YouTube, Hacker News, dev.to, Medium, and other public discourse platforms. API-free; uses WebSearch with platform-targeted site operators plus recency filters. Produces DISCOURSE.md (a structured brief) and JSON output the writer can consume. Complements blog-researcher (which focuses on authority sources) with a recency-and-engagement lens. Use when user says "blog discourse", "discourse research", "what are people saying about", "research what people are saying", "voice of customer", "soci
npx skills add AgriciDaniel/claude-blog --skill blog-discourse --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Blog Discourse: Real Discourse Research, API-Free Produces DISCOURSE.md: a structured brief of what practitioners said about <topic> on the public web in the last 30 days. It is the recency + engagement lens that `blog-researcher` (authority-first) lacks, asking what practitioners and customers are actually saying about this topic right now. Adapted from the methodology of `last30days-skill` (Matt Van Horn, MIT, https://github.com/mvanhorn/last30days-skill). The upstream uses platform APIs; this sub-skill uses WebSearch with platform-targeted site operators. No API keys required. ## Commands | Command | Purpose | |---|---| | `/blog discourse <topic>` | Produce a discourse brief at project-root `DISCOURSE.md` | | `/blog discourse <topic> --days 90` | Widen the freshness window from 30 to 90 days | | `/blog discourse <topic> --input results.json` | Skip search; build the brief from a pre-gathered results file. The flag name matches `scripts/discourse_research.py --input` directly. | | `/blog discourse <topic> --output path.md` | Write markdown to a chosen output path and print structured JSON without markdown to stdout. | | `/blog discourse <topic> --format json` | Print the full J
- Commands
- Workflow
- Phase 0: Topic Pre-Flight (mandatory)
- Phase 1: Topic Decomposition (Step 0.55)
- Phase 2: Platform-Targeted WebSearch
- Phase 3: Result Collection
- Phase 3.5: WebSearch Untrusted-Data Contract (mandatory)
- Phase 4: Brief Generation (Python helper)
- Phase 5: Synthesis Output
- DISCOURSE.md Output Shape
- Composition with other sub-skills
- Relationship to other research skills
- Error Handling
- Attribution
write JSON to "$RESULTS_JSON" then pass it to the script python3 scripts/discourse_research.py \
What does the blog-discourse skill do?
Research what people are actually saying about a topic in the last 30 days across Reddit, X / Twitter, YouTube, Hacker News, dev.to, Medium, and other public discourse platforms. API-free; uses WebSearch with platform-targeted site operators plus recency filters. Produces DISCOURSE.md (a structured brief) and JSON output the writer can consume. Complements blog-researcher (which focuses on authority sources) with a recency-and-engagement lens. Use when user says "blog discourse", "discourse research", "what are people saying about", "research what people are saying", "voice of customer", "soci
How do I install it?
Run `npx skills add AgriciDaniel/claude-blog --skill blog-discourse --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From AgriciDaniel/claude-blog, a repository with 1,566 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.