aim-status

Check AI Memory module health, statistics, and system state. ## 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. ```bash "${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" aim_status.py ``` When working from an `ai-memory` repo checkout, `./scripts/memory/run-with-env.sh ...` is an equivalent contributor shortcut. ## Examples Run one command at a time as needed: ```bash "${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" aim_status.py --section sync "${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" aim_status.py --section freshness "${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" aim_status.py --section decay "${AI_MEMORY_INSTALL_DIR:-$HOME/.ai-memory}/scripts/memory/run-with-env.sh" aim_status.py --section flags ``` ## Implementation - Script: `scripts/memory/aim_status.py` - Output budget: `< 2K tokens` - Behavior: section-aware status report with graceful fallback when services or data are unavailable ## Activation ```text /aim-status /aim-status --section sync /aim-status --section freshness /aim-status --section decay /aim-status --section flags ``` ## Output Sections ### Health Shows service availability for Qdrant, Embedding service, and Monitoring API. ### Collections Point counts per collection: - **code-patterns** - Project-specific implementation patterns - **conventions** - Cross-project shared conventions - **discussions** - Decision context and session summaries ### Services Detailed service status with port numbers. ### Sync Status GitHub synchronization state from the shared install state file in `~/.ai-memory/github-state/` for the current repo: - Last sync time (with relative time) - Items synced (with breakdown by type) - Error count - GitHub Sync enabled/disabled Fallback: "No sync history found" if state file doesn't exist. ### Freshness Summary Code-patterns freshness classification from `run_freshness_scan()`: - **Fresh** - Content matches, low commit activity - **Aging** - Some commit activity since stored - **Stale** - Significant commit activity - **Expired** - High activity or content changed Fallback: "Freshness scan unavailable" if no git context. ### Decay Distribution Temporal decay score distribution from a 50-vector sample per collection. Decay formula: `temporal_score = 0.5 ^ (age_days / half_life)` Bucketed into 5 bands: 0.8-1.0 (fresh), 0.6-0.8 (recent), 0.4-0.6 (aging), 0.2-0.4 (old), 0.0-0.2 (stale). Fallback: "Decay distribution unavailable" if sampling fails. ### System Flags Key feature toggles from configuration: - **Auto-update**: `auto_update_enabled` - **Freshness**: `freshness_enabled` - **GitHub Sync**: `github_sync_enabled` - **Parzival**: `parzival_enabled` ## Notes - Output budget: < 2K tokens total - Each section handles graceful fallback when data unavailable - Qdrant connection uses port 26350 with API key authentication - Metrics pushed via `push_skill_metrics_async` on completion