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OpenClaw's daily-ai-news cron job kept timing out. The root cause wasn't a weak model, bloated prompt, or upstream API failure — it was a missing absolute path in the SKILL.md, causing the Agent to spend 15 exec calls searching for a tool's location every run. Message count ballooned from 54 to 165, tool results from 204KB to 1.1MB. This is the full debugging story.
OpenClaw's vector retrieval silently failed — but BM25 text search kept the memory system running for two weeks unnoticed. When you discover 'it works without embeddings,' should you even bother fixing it? Here's how I used NVIDIA's free embedding API to complete the picture, and what I learned about when vector search actually matters.
A full-chain production battle log: from startup failures and Feishu message silent drops to production stability — compaction safeguard, five-layer debugging, model-harness fit, and memory system comparison.