Four days, multiple form submissions, and one firm email to escape the automation loop.
In my original project, I also created dedicated testing slash commands like /test-cli that run full verification against live data. The agent executes live queries and commands and reasons about whether the results are correct and writes Markdown files with tables, timestamps, and diagnostic notes. What’s great about this is that the agent can investigate issues on the spot so by the end, the result comes back diagnosed.
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Race conditions hide twice as long as other bugs. Traditional fuzzers miss them. This validates ML-based detection.
CRDF maintains a dedicated false positives form requiring no account creation. I submitted details and received a response the next morning: