aim-freshness-report
CommunityDetect stale AI memories.
Software Engineering#ai memory#memory management#code patterns#code freshness#github sync#stale data
AuthorHidden-History
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the issue of "AI amnesia" by identifying outdated or irrelevant information stored in the AI's memory, ensuring the AI operates with the most current and accurate context.
Core Features & Use Cases
- Staleness Detection: Compares stored code patterns against the latest GitHub code blobs to identify memories that may no longer be accurate due to code changes.
- Tiered Reporting: Categorizes memories into 'Fresh', 'Aging', 'Stale', and 'Expired' based on commit activity and content changes.
- Actionable Insights: Provides specific recommendations for updating or re-capturing stale memories.
- Use Case: A developer can run this skill to quickly identify which of their AI-assisted code snippets or architectural decisions are no longer aligned with the current codebase, preventing the AI from acting on outdated information.
Quick Start
Run the aim-freshness-report skill to scan all projects for stale memories.
Dependency Matrix
Required Modules
None requiredComponents
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: aim-freshness-report Download link: https://github.com/Hidden-History/ai-memory/archive/main.zip#aim-freshness-report Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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