aim-refresh
SkillDocs & knowledgeManually re-evaluate freshness for code-patterns memories
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the aim-refresh skill
What this skill tells your AI
The instructions your AI receives, as published by hidden-history/ai-memory in .claude/skills/aim-refresh/SKILL.md and read by ahel’s review.
Manually re-evaluates freshness for code-patterns memories. Reuses the freshness scan pipeline from SPEC-013 with optional scope filters.
Canonical Execution
Always run the real script through run-with-env.sh so the skill uses the
installed ai-memory virtualenv and the standard local service defaults.
"${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" refresh.py
Examples
# Scan all code-patterns memories
"${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" refresh.py
# Limit to a specific project group_id
"${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" refresh.py my-project
# Topic filter (v2.1 — currently runs full scan with project filter)
"${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" refresh.py --topic "authentication"
Implementation
- Script:
scripts/memory/refresh.py - Interpreter:
run-with-env.sh(importsmemory.*, requires venv) - Args:
[project](optional positional group_id filter),--topic(v2.1, no-op today) - Output: tier table (Fresh / Aging / Stale / Expired / Unknown) + actionable count
Signals
- GitHub stars
- 41
- Forks
- 5
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
aim-refresh- Source
- github.com/hidden-history/ai-memory