- name
- aim-settings
- description
- Display current memory system configuration and settings
- allowed-tools
- Read
# Memory Settings - Configuration Viewer
Display the current configuration of the AI Memory Module, including collections, types, thresholds, token budgets, and service endpoints.
## Activation
```text
# Show all memory settings
/aim-settings
# Show specific section
/aim-settings --section collections
/aim-settings --section types
/aim-settings --section thresholds
/aim-settings --section services
/aim-settings --section agents
```
## Configuration Sections
### Collections
Shows the 3 Memory System V2.0 collections:
- **code-patterns** - Project-specific implementation patterns
- **conventions** - Cross-project shared conventions
- **discussions** - Decision context and session summaries
### Memory Types (14 total)
Organized by collection:
- code-patterns: `implementation`, `error_fix`, `refactor`, `file_pattern`
- conventions: `rule`, `guideline`, `port`, `naming`, `structure`
- discussions: `decision`, `session`, `blocker`, `preference`, `context`
### Thresholds
- **similarity_threshold** - Minimum relevance score for search results (default: 0.7)
- **dedup_threshold** - Similarity threshold for duplicate detection (default: 0.95)
- **max_retrievals** - Maximum memories per search (default: 5)
- **token_budget** - Maximum tokens for context injection (default: 4000, per BP-039)
### Services
Shows connection details for:
- **Qdrant** - Vector database (default: localhost:26350)
- **Embedding Service** - Jina AI embeddings (default: localhost:28080)
- **Monitoring API** - Health checks and metrics (default: localhost:28000)
- **Streamlit Dashboard** - Web UI (default: localhost:28501)
- **Grafana** - Metrics visualization (default: localhost:23000)
- **Prometheus** - Metrics storage (default: localhost:29090)
- **Pushgateway** - Metrics push gateway (default: localhost:29091)
### Agent Token Budgets
Shows token allocation per BMAD agent:
- architect: 1500 tokens
- analyst: 1200 tokens
- pm: 1200 tokens
- developer/dev: 1200 tokens
- solo-dev: 1500 tokens
- quick-flow-solo-dev: 1500 tokens
- ux-designer: 1000 tokens
- qa: 1000 tokens
- tea: 1000 tokens
- code-review/code-reviewer: 1200 tokens
- scrum-master/sm: 800 tokens
- tech-writer: 800 tokens
- default: 1000 tokens
### Logging
- **log_level** - Logging verbosity (default: INFO)
- **log_format** - Log output format (json or text, default: json)
### Collection Size Limits
- **Warning threshold** - 10,000 points
- **Critical threshold** - 50,000 points
## Activation Examples
```text
# View complete configuration
/aim-settings
# Check current thresholds
/aim-settings --section thresholds
# View service endpoints
/aim-settings --section services
# Check agent token budgets
/aim-settings --section agents
# View all memory types
/aim-settings --section types
```
## Python Configuration Reference
Configuration is managed by `src/memory/config.py`:
```python
from src.memory.config import get_config, AGENT_TOKEN_BUDGETS, get_agent_token_budget
# Get configuration singleton
config = get_config()
# Access settings
print(f"Qdrant: {config.qdrant_host}:{config.qdrant_port}")
print(f"Similarity threshold: {config.similarity_threshold}")
print(f"Max retrievals: {config.max_retrievals}")
# Get agent-specific token budget
budget = get_agent_token_budget("architect") # Returns 1500
```
## Environment Variables
Configuration can be customized via environment variables or `.env` file:
```bash
# Core thresholds
SIMILARITY_THRESHOLD=0.7 # Retrieval relevance cutoff
DEDUP_THRESHOLD=0.95 # Duplicate detection sensitivity
MAX_RETRIEVALS=10 # Results per search
TOKEN_BUDGET=4000 # Context injection limit (per BP-039)
# Service endpoints
QDRANT_HOST=localhost
QDRANT_PORT=26350
EMBEDDING_HOST=127.0.0.1
EMBEDDING_PORT=28080
MONITORING_HOST=localhost
MONITORING_PORT=28000
# Logging
LOG_LEVEL=INFO # DEBUG, INFO, WARNING, ERROR, CRITICAL
LOG_FORMAT=json # json or text
# Collection size limits
COLLECTION_SIZE_WARNING=10000
COLLECTION_SIZE_CRITICAL=50000
```
## Configuration Precedence
Settings are loaded in this order (highest priority first):
1. Environment variables
2. `.env` file in project root
3. Default values
## Output Format
The skill displays configuration in organized sections with:
- Current values
- Default values (if different)
- Validation ranges (for thresholds)
- Service URLs with ports
- Memory type mappings to collections
## Technical Details
- **Type Safety**: Uses pydantic-settings v2.6+ for validation
- **Immutable**: Configuration is frozen (thread-safe)
- **Singleton**: Single config instance per process (lru_cache)
- **Validation**: All thresholds validated on load
## Related Skills
- `/aim-search` - Use these settings for memory search
- `/aim-status` - Check system health and statistics
## Notes
- Configuration is loaded once at startup
- Changes to .env require service restart
- All ports use 2XXXX prefix to avoid conflicts
- Token budgets optimized per agent role (architects need more context than scrum masters)
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