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aim-settings
Display current memory system configuration and settings
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Display current memory system configuration and settings
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | aim-settings |
| description | Display current memory system configuration and settings |
| allowed-tools | Read |
Display the current configuration of the AI Memory Module, including collections, types, thresholds, token budgets, and service endpoints.
# 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
Shows the 3 Memory System V2.0 collections:
Organized by collection:
implementation, error_fix, refactor, file_patternrule, guideline, port, naming, structuredecision, session, blocker, preference, contextShows connection details for:
Shows token allocation per BMAD agent:
# 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
Configuration is managed by src/memory/config.py:
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
Configuration can be customized via environment variables or .env file:
# 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
Settings are loaded in this order (highest priority first):
.env file in project rootThe skill displays configuration in organized sections with:
/aim-search - Use these settings for memory search/aim-status - Check system health and statisticsDetect content drift of an operator's scaffolded sanctum files (BOND, CAPABILITIES, CREED, INDEX, LORE, MEMORY, PERSONA, PULSE) against the evolving reference templates, and surface recommended add/remove WITH rationale — never a silent overwrite. Use on a session-start drift check, after the reference templates change, or when the operator asks whether their sanctum is current.
Check ai-memory system status and collection stats
Check ai-memory system status and collection stats
Manually save current session context to ai-memory
Search ai-memory for relevant stored memories
Search ai-memory for relevant stored memories