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Reddit Post & Comment Tree to LLM Markdown.
Paste any Reddit URL or post_id to extract the original post, upvote scores, and indented comment hierarchy into clean Markdown ready for Claude, ChatGPT, Cursor, or vector embeddings — with live token counting.
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# New rule banning a SaaS product category — community discussion
- **Subreddit:** r/SaaS | **Author:** u/saas_mod_team | **Score:** 342 (94% upvoted)
- **Source:** /r/SaaS/comments/1u0z4vz/new_rule_banning_a_saas_product_category_no/
## Original Post
We are updating r/SaaS self-promotion rules to keep technical founder postmortems, unit economics breakdowns, and real customer discovery threads front and center.
## Top Community Comments (3 extracted, sorted by top)
- **[+128] u/b2b_bootstrapped:** Finally. High-signal founder teardowns and real churn numbers are the entire reason we read r/SaaS every morning.
- **[+49] u/rag_infra_dev:** Agreed — especially threads comparing real API costs vs building scrapers in-house.
- **[+19] u/saas_mod_team *(OP)*:** Appreciate the feedback! Technical benchmarks and open-source tools remain 100% welcome.Production REST API · GET /v1/posts/comments
Ingest full nested threads into RAG pipelines via REST API
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Reddit to LLM Markdown FAQ
How does this Reddit to LLM Markdown converter preserve nested reply hierarchies?
It queries GET /v1/posts/detail and GET /v1/posts/comments on api.forumdataapi.com, indenting every reply according to its integer depth (0, 1, 2...) alongside author handles and upvote scores so LLMs understand who replied to whom.
Can I automate this Reddit-to-Markdown conversion in Python or Node.js?
Yes. Click 'Copy cURL' or 'Copy Python' inside the converter or grab a free rd_live_ API key (12,000 free credits · $1.20) to convert thousands of threads at $0.10 per 1,000 comments.