Social media decision

CommentHunter.click - Extract Social Media Comments

A competent developer can build a limited comment-extraction tool, but reproducing the full product (multi-site polish, scale, legal/partnerships) is non-trivial and better kept paid for most teams.

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Built by Max Hamal 🇺🇦, who ships 8 products in this index

You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$100one-off42 h to build

$40/mo3 h/mo upkeep

No published price to break even against.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All CommentHunter.click - Extract Social Media Comments alternatives, with the arithmetic →

What a replacement has to do

  • Connect to a social account or scrape a public post, fetch comments (with pagination and rate-limit handling), store results, normalize/dedupe, export or analyze.

What it still won’t have

  • polished multi-site integrations and error-handling at scale
  • commercial SLA, uptime and monitoring
  • legal/compliance and platform partnership support
  • ongoing UI/UX polish and customer support

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

CommentHunter.click - Extract Social Media Comments does not publish a price we could read, so there is nothing to compare against. What building costs is below.

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal CommentHunter replacement: use Node.js + Playwright for scraping, Express for API, Postgres for storage, and Docker for deployment. Scope: implement connectors for two target social sites (OAuth if available, otherwise headless scraping), paginated comment fetching with retries and rate-limit backoff, store comments and user metadata in Postgres, deduplicate/normalize records, and provide CSV/JSON export plus a one-endpoint sentiment summary (VADER). Out of scope: multi-account team management, billing, advanced UI. Include error handling, logging, unit tests for fetch and dedupe logic, and a Docker Compose setup for local dev.
How we checked2 sources · 3/3 runs agreed · evidence score 62

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 2 cited sources+1
  • 3/3 assessment runs agreed+4
  • Evidence score62

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 2

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded