Individual skill
evo-memory
Manages persistent research memory across ideation and experimentation cycles. Maintains two stores: Ideation Memory M_I (feasible/unsuccessful directions) and Experimentation Memory M_E (reusable strategies for data processing, model training, architecture, debugging). Three evolution mechanisms: IDE (after research-ideation), IVE (after experiment failure — classifies failures as implementation vs fundamental), ESE (after experiment success — extracts reusable strategies). Use when: updating memory after completing research-ideation cycles or experiment pipelines, classifying why a method failed (implementation vs fundamental failure), starting a new research cycle needing prior knowledge, user mentions 'update memory', 'classify failure', 'what worked before', 'research history', 'evolution'. Do NOT use for running experiments (use experiment-pipeline), debugging experiment code (use experiment-craft), or generating ideas (use research-ideation).
skills/evo-memory/SKILL.md
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- Last checked
- Nov 4, 2026
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- 488
- Repository last updated
- Oct 27, 2026
- License
- Apache-2.0
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- skills Repository topic
- ai-agent Repository topic
- ai4science Repository topic
- vibe-research Repository topic
- core Declared skill tag
- meta-learning Declared skill tag
- engineering Derived category
- data Derived category
- testing Derived category
- research Derived category
- education Derived category
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SKILL.mdcore · 19,134 bytesassets/evolution-report-template.mddoc · 1,169 bytesassets/experiment-memory-template.mddoc · 1,179 bytesassets/ideation-memory-template.mddoc · 2,061 bytesreferences/ese-protocol.mddoc · 9,613 bytesreferences/ide-protocol.mddoc · 7,313 bytesreferences/ive-protocol.mddoc · 11,610 bytesreferences/memory-schema.mddoc · 13,480 bytesreferences/paper-prompts.mddoc · 10,328 bytes
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# Evo-Memory
A persistent learning layer that accumulates research knowledge across ideation and experimentation cycles. Maintains two memory stores and implements three evolution mechanisms that feed learned patterns back into future research.
## When to Use This Skill
- User has completed an `research-ideation` and needs to update Ideation Memory
- User has completed (or failed) an `experiment-pipeline` and needs to update memory
- User is starting a new research cycle and wants to load prior knowledge
- User asks about research memory, learned patterns, or cross-cycle knowledge
- User mentions "evo-memory", "update memory", "what worked before", "research history", "evolution"
## The Learning Layer