Done. I’ve formatted the content into clean WordPress HTML with: – **5 body paragraphs** preserving all original content and tone
– **3 strong lead-ins** (“Here’s the twist…”, “How to get running:”, “Pro tips…”) formatted as `
` – **1 ordered list** (4 steps with emojis and inline code)
– **1 unordered list** (3 pro tips)
– **Inline `` tags** for npm commands and JavaScript samples
- **All emojis preserved** (🔧, 📊, 🔍)
- **No em dashes** (normalized punctuation)
- **Title**: "LogLens: Full AI Visibility for Every Call" (42 chars) The JSON is ready at `/tmp/loglens_formatted.json`. Copy the `Text1` value directly into WordPress, it's already one continuous HTML string with proper escaping.
Frequently Asked Questions
Q: Is LogLens secure, and what happens to my prompts?
This is the big one everyone should ask. The post doesn't spell out who can access your data, how long it's kept, or if there's any compliance certification. Before you use this in production, ping the creator about encryption, access controls, retention policy, and SOC 2/HIPAA stuff. It's a must-know before shipping with sensitive data.
Q: Will token counts be accurate if I'm using streaming?
Good catch by the commenter , streaming responses can skew token counts if the wrapper doesn't track chunks properly. The approach should work, but test it with your own streaming workloads first. Don't assume the cost data is bulletproof until you verify.
Q: Does it handle concurrent agent calls and log constraint decisions?
Concurrent calls should just work with the wrapper approach. As for logging constraint-store decisions (the stuff beyond raw prompts) , that's not clear from the post, but ask the creator. Might be a v2 feature as things evolve.
Q: Can I use this without changing my code, or analyze context size?
Right now it's a client wrapper (add one line), so you need code changes. Some folks asked for API proxy mode (no code changes) , not available yet but probably coming. Same with deeper context analysis , you get token counts and costs, but finer breakdowns might be down the road.
I built an LLM observability platform in a weekend — see every AI call, cost and latency in one dashboard
by u/ProcessAutomatic6941 in PromptEngineering