crucible-emergent-resurrection

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a hypothesis has failed and needs archiving with resurrection conditions, when reviewing dormant ideas for possible revival, when.

AI & Automation 62 stars 9 forks Updated today MIT

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Skill Content

# Emergent Resurrection — negative-knowledge archive > **Self-Evolving Skill**: If the failure taxonomy misses a mode, or a resurrection trigger type recurs, update the relevant section AND append to `references/evolution-log.md`. Don't defer. Failed hypotheses are not waste. They are negative knowledge that: 1. Documents the investigation's boundaries 2. Prevents re-exploring known dead ends 3. Can come back when conditions change This skill is the genetic-evolutionary mechanism for "**don't rule out anything we have tried, as long as it can emerge through iterative process**". --- ## Why NOT just delete failed ideas The session accumulated 17 null campaigns. Without negative-knowledge capture, we would: - Re-explore the same dead ends in future sessions (wasted compute) - Lose the meta-lesson each failure taught (wrong null, wrong scaling, wrong scope) - Be unable to detect when conditions have shifted enough to retry Failed attempts are cheaper to preserve than to re-run. --- ## Failure-mode taxonomy Each failed campaign fits one or more modes. Classification determines resurrection conditions. | Failure mode | Description | Resurrection trigger | | ------------------------- | -------------------------------------------------------- | ----------------------------------------------------------------------------------------------- ...

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Author
terrylica
Repository
terrylica/cc-skills
Created
8 months ago
Last Updated
today
Language
Shell
License
MIT

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