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[return to "How does misalignment scale with model intelligence and task complexity?"]
1. anupam+lF[view] [source] 2026-02-03 05:56:10
>>salkah+(OP)
The "natural overthinking increases incoherence" finding matches my daily experience with Claude.

I maintain ~100 custom skills (specialized prompts). Sometimes Claude reads a skill, understands it, then overthinks itself into "helpful" variations that break the workflow.

Has anyone else found prompt density affects coherence?

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2. anupam+xL1[view] [source] 2026-02-03 14:19:33
>>anupam+lF
Following up - I built a tool "wobble"[1] to measure this: parses ~/.claude/projects/*.jsonl session transcripts, extracts skill invocations + actual commands executed, calculates Bias/Variance per the paper's formula.

Ran it on my sessions. Result: none of skills scored STABLE. The structural predictors of high variance: Numbered steps without clear default, Options without (default) marker, Content >4k chars (overthinking zone), Missing constraint language

[1] https://github.com/anupamchugh/shadowbook (bd wobble)

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