# $DOXA Social Sentiment & Intelligence — 2026-08-08 14:30 UTC

> **Asset:** $DOXA  
> **Momentum Status:** Fading Quickly  
> **Timestamp:** 2026-08-08 14:30 UTC (2026-08-08T14:30:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-08-08-14-30/crypto/DOXA  
> **Overview Brief:** https://cryptitalk.com/2026-08-08-14-30/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 1
- **Total Impressions:** 106
- **Likes:** 13
- **Retweets:** 6
- **Comments:** 6

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 6, Retweets: 6, Likes: 13, Impressions: 106


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## Cited Community Posts & Evidence


### Post #1 by @Cripson01
> **Author:** [@Cripson01](https://x.com/Cripson01)  
> **Metrics:** 50 likes · 0 retweets · 25 comments · 321 views  


> **Source Link:** [https://x.com/Cripson01/status/2086015598140547291](https://x.com/Cripson01/status/2086015598140547291)  


> **Visual Context:** Infographic titled 'Understanding an LLM Request on Ritual' showing the process flow: Prompt → messages.json → ABI Encoding → Calldata → LLM Precompile 0x0802 → TEE Inference → Response, with three components labeled Transaction, Context, and Compute.  

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> "One interesting thing to understand about LLM inference on Ritual:

There are multiple resource layers involved in a single LLM request.

When a contract calls Ritual’s LLM precompile at 0x0802, the request uses an OpenAI-compatible messagesJson format and is ABI-encoded before"




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## Contributing Accounts

- `@dinodoxa` (https://x.com/dinodoxa)