flowchart TD
PR["Pull request"] --> Recall["Recall repo conventions and prior lessons"]
Recall --> Review["OpenClaw review agent"]
Review --> Comment["Findings, fixes, and review summary"]
Comment --> WriteBack["Write reusable repo memory"]
WriteBack --> Queue["Maintainer review queue"]
Queue --> NextPR["Next PR review is more repo-specific"]
This is the flagship Agent Memory workflow. A stateless reviewer catches a bug once. A memory-backed reviewer keeps repo-specific lessons, maintainer corrections, false positives, and testing expectations available for future reviews.
Built by Nate B. Jones / OB1. Follow Nate for practical AI systems, agent workflows, and implementation notes: Substack and natebjones.com.
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Complete NBJ OB1 Agent Memory for OpenClaw.
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Configure the OpenClaw plugin with the target OB1 workspace and project.
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Install the live OpenClaw skill:
openclaw skills install nbj-ob1-agent-memory-openclaw
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Call recall before reviewing a PR.
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Write back compact lessons and artifact references after review.
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Use Safe Agent Memory and Provenance when deciding whether review lessons can become instruction-grade.
Recall these memory types:
- repo conventions
- prior review comments
- recurring bug patterns
- risky files or subsystems
- test expectations
- security-sensitive patterns
- maintainer preferences
Write back these categories:
- new recurring issue patterns
- review decisions
- fixes applied
- tests that caught or missed the issue
- maintainer corrections
- false positives to avoid
Do not store the full diff or raw review transcript. Store PR, commit, file, or issue references.
- Repeated reviews retrieve confirmed repo memory.
- Inferred review lessons remain evidence-only until confirmed.
- Maintainer corrections can supersede older lessons.
- False positives are stored as review guidance, not permanent bans.
- Recall traces show which memories influenced review output.