We Built a General Reddit Search Skill for Claude

We shipped a second packaged skill — reddit-search — for the other half of what people actually use the ThreadSnoop API for. reddit-lead-finder answers “who on Reddit needs my product?” This one answers everything else: what are people saying about a topic, a brand, or a competitor, and is anyone watching a given subreddit for a specific kind of post. No product required, no fixed scoring rubric — just relevance to whatever you actually asked, stated plainly in the report instead of forced through a rubric built for a different job.

Why this needed its own skill

reddit-lead-finder's rubric — Customer Fit, Problem Severity, Purchase Intent — is deliberately narrow: it only makes sense if there's a product being sold. Ask it to research sentiment on a competitor or watch a subreddit for a general topic and the rubric actively gets in the way; every result gets forced through a lens that doesn't apply. reddit-searchdrops the fixed rubric entirely — it judges relevance against your actual request and says what criteria it used, per report, since that changes with what you're asking.

What it actually does

• Takes any topic, brand, competitor, or subreddit — not tied to a product or an ICP.
• States its own relevance criteria per report instead of applying one fixed rubric to every kind of request.
• Handles Reddit's hidden vote counts on fresh content correctly— posts and comments under roughly 36 hours old report a placeholder score, not a real one; scoring on it anyway produces confidently wrong rankings, so the skill flags “new” content instead of ranking it on a number that isn't real yet.
• Skips or flags removed and deleted content instead of quoting it as if it were still there.
• Produces a ranked report, not a data dump — no reply drafting, no auto-posting, commenting, or DMs.

Two of those — the fresh-content scoring trap and a tool-output size limit that truncated results on any moderately active subreddit — were real bugs caught live-testing the skill against real subreddits, not theoretical edge cases. Both are fixed in what ships today.

A real run, unscripted

We asked it to look into a new model release — “Look for information about the new Kimi K3 model by Moonshot” — and it searched the relevant communities without being told which ones:

“Minimum BoM to run Kimi K3. 2304 GB VRAM, 512 GB host RAM, spread across 4 hosts... TOTAL £45,424.”
— r/LocalLLaMA

Ranked top because it was the most substantive reaction in the run — a genuinely detailed, quantified cost breakdown, not just an opinion — which is exactly the kind of judgment call a fixed rubric can't make, because “substantive” isn't one of its categories.

Get it

Both files are free downloads from the ThreadSnoop skills page, no signup required to grab them — you'll need a free API key to actually run it (1,000 free Reddit searches on signup, no card):

Claude Code — one command:

npx skills add threadsnoop/reddit-skills --skill reddit-search -a claude-code -g

Drop -g to scope it to just one project instead.

Claude Desktop or claude.ai — connect the ThreadSnoop MCP server first (Settings → Connectors → Add custom connector, a real OAuth flow — see the Desktop or web walkthrough), then download reddit-search.zip from Customize → Skills and turn it on.

Claude Code, Claude Desktop, and Claude.ai web are all confirmed working end to end.

Frequently asked questions