Agent skill · Backend & API

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

Infrasity-Labsgithub.com/Infrasity-LabsGitHub ↗
claude-codeMIT
Install
npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill blog-discourse --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 12 KB
Bundled scripts: none
Path: .claude/skills/blog-discourse/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 97
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Blog Discourse: Real Discourse Research, API-Free `blog-discourse` is the recency + engagement lens that `blog-researcher` (authority-first) lacks. It asks: in the last 30 days, what are practitioners and customers actually saying about this topic on the public web? 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> --feed-into brief` | Run the brief, then immediately invoke `/blog brief <topic>` with DISCOURSE.md auto-loaded | | `/blog discourse <topic> --feed-into write` | Run the brief, then invoke `/blog write <topic>` | | `/blog discourse <topic> --feed-into strategy` | Run the brief, then invoke `/blog strategy <topic>` | | `/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. | ## Workflow ### Phase 0: Topic Pre-Flight (mandatory) Before any search, run the four

What's inside
Steps it walks through
  1. Commands
  2. Workflow
  3. Phase 0: Topic Pre-Flight (mandatory)
  4. Phase 1: Topic Decomposition (Step 0.55)
  5. Phase 2: Platform-Targeted WebSearch
  6. Phase 3: Result Collection
  7. Phase 3.5: WebSearch Untrusted-Data Contract (mandatory)
  8. Phase 4: Brief Generation (Python helper)
  9. Phase 5: Synthesis Output
  10. DISCOURSE.md Output Shape
  11. Composition with other sub-skills
  12. Relationship to other research skills
  13. Error Handling
  14. Methodology Note
Commands it runs
write JSON to "$RESULTS_JSON" then pass it to the script
python scripts/discourse_research.py \
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About this skill
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 Infrasity-Labs/dev-gtm-claude-skills --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 Infrasity-Labs/dev-gtm-claude-skills, a repository with 97 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.

Keep going