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Create a CI harness to auto-detect and mark archetype drift when changes break it #4100

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@squid-protocol

We have a wonderful repo, file and function classification system based on k-means clustering on file metrics sans extension, so we can cluster these extractions by structure and not language. But we've also been rapidly improving the engine, quality of detection, etc. I'm worried that we aren't correctly monitoring drift in that system when we grow and potentially are reporting incorrect archetype classifications.

This is an important gap we should explicitly monitor and put into the ML archetype meta data if it was validated or not. So the system know's it's trustworthy for that version.

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  1. added
    data-integrityIssues relating to RAM state or SQLite database fidelity
    core-engineModifications to the central physics and parsing engine
    priority: highCore feature broken, but workarounds exist
    on Oct 2, 2026
  2. added a commit that references this issue on Oct 2, 2026
  3. added 2 commits that reference this issue on Oct 2, 2026
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    core-engineModifications to the central physics and parsing enginedata-integrityIssues relating to RAM state or SQLite database fidelitypriority: highCore feature broken, but workarounds existscope:infraCI, tooling, churn/factory, docs infrastructure

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