Claude Code Help Channel Aggregator

Aggregate Claude Code help discussions from across the web - Reddit (r/ClaudeAI, r/Anthropic) and GitHub Discussions on anthropics/claude-code and related repos - cluster recurring questions, and surface the top Q&A patterns with example threads and where they got answered. Built for documentation teams and support engineers who want to find FAQ gaps fast.

Part of Ian Mu's 100-actor portfolio at github.com/ianymu. Inspired by the post-Stop self-verification flow at github.com/ianymu/claude-verify-before-stop.

What does Claude Code Help Channel Aggregator do?

Given a list of sources (Reddit subreddits, GitHub repos with Discussions), the Actor pulls all question-style threads created within the last N days, normalizes their titles, extracts keyword fingerprints, and clusters threads that ask the same thing. Each cluster is ranked by frequency + engagement (upvotes + comment count) and the top N clusters are emitted to the dataset along with 3 example threads per cluster and a hint about how the question was answered (accepted answer, comment count, or 'none'). Discord is intentionally excluded because the official Claude Code Discord is invite-only and private.

Apify platform advantages: built-in cron scheduling, dataset API access, retry handling, integrations with Slack and webhooks - all included so you can wire the output straight into your docs CMS or a weekly digest.

Why use Claude Code Help Channel Aggregator?

• FAQ gap detection: Find which questions keep recurring weekly and write them into the docs once and for all.
• Support engineering: Build a canned-answer playbook from the real questions users ask.
• Product feedback loop: Surface the same bug/confusion appearing across Reddit and GitHub Discussions simultaneously.
• Documentation prioritization: Rank by rankScore to know what to write first.

How to use Claude Code Help Channel Aggregator

1. Open the Input tab.
2. Accept the defaults (last 30 days, Reddit + GitHub Discussions) or customize sources/subreddits/repos.
3. For GitHub Discussions, add a GITHUB_TOKEN environment variable on the Actor's Settings tab (any GitHub personal access token with public-repo scope works). Without it, only Reddit is scanned.
4. Hit Start. Reddit is unauthenticated and rate-limited; GitHub uses the GraphQL API.
5. Inspect the Output tab. Each row = one question cluster with examples and a rank score.
6. Schedule it weekly to track shifts in the help conversation over time.

Input

Field	Type	Default	Description
sources	array	["reddit", "github-discussions"]	Channels to aggregate.
daysBack	int	30	How many days back to scan.
subreddits	array	["ClaudeAI", "Anthropic"]	Subreddits without the r/ prefix.
githubRepos	array	3 anthropics/* repos	owner/name format. Requires GITHUB_TOKEN.
topN	int	25	Top N clusters to return.

Output

Each dataset item is one question cluster:

{
  "clusterKey": "error|claude|code|terminal",
  "keywords": ["error", "claude", "code", "terminal", "node"],
  "questionCount": 7,
  "totalScore": 41,
  "totalComments": 23,
  "sources": ["reddit", "github-discussions"],
  "rankScore": 24.6,
  "examples": [
    {
      "title": "Claude Code errors out on Node 18 in WSL2 - what's the fix?",
      "url": "https://www.reddit.com/r/ClaudeAI/comments/abc123/...",
      "source": "reddit",
      "sourceId": "r/ClaudeAI",
      "score": 12,
      "commentCount": 5,
      "answeredBy": "5 comment(s)",
      "createdAt": "2026-05-12T08:15:00Z"
    }
  ]
}

You can download the dataset in JSON, HTML, CSV, or Excel.

Data table

Field	Meaning
clusterKey	Sorted keyword fingerprint used to merge similar questions
keywords	Top extracted keywords for this cluster
questionCount	How many threads belong to this cluster
totalScore	Sum of upvotes across cluster threads
totalComments	Sum of comments across cluster threads
sources	Which sources contributed to this cluster
rankScore	Frequency + log-engagement composite score for sorting
examples	Up to 3 representative threads with title, URL, score, and how-it-was-answered

Pricing / Cost estimation

A typical run (2 subreddits + 3 GitHub repos, 30 days) is well under one compute unit on Apify Free; runtime is a couple minutes. Weekly scheduling stays comfortably inside the free tier.

Tips and advanced options

• Token in env: Add GITHUB_TOKEN via Actor Settings > Environment variables. The Actor reads process.env.GITHUB_TOKEN.
• Tighter clusters: shorten daysBack to 7 to get a true 'this week' view.
• More repos: append community-maintained Claude Code repos to githubRepos to widen coverage.
• Discord caveat: official Claude Code Discord is invite-only; we do not scrape it. If you have a public mirror, treat it as another 'subreddit' equivalent in your own fork of this Actor.

FAQ, disclaimers, and support

• Public data only. Reddit and GitHub public posts are used; no private channels.
• Rate limits. Reddit is 1 req/1.5s unauthenticated; GitHub GraphQL is bounded by token rate limits.
• Clustering is heuristic. Keyword-fingerprint clustering merges most paraphrases but isn't semantic; the examples field always lets you verify.
• Issues / feature requests: open an issue at github.com/ianymu.
• Verification methodology: developed with the post-Stop verification flow at github.com/ianymu/claude-verify-before-stop.

Author: Ian Mu - One-person AI company experiments at github.com/ianymu.