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。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/majiayu000/claude-skill-registry --skill aim-settings命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
LLM token logprobs and calibration. Per-decision confidence, ECE, Brier, reliability diagrams, low-confidence triage.
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
回顾最近 N 天的 Claude Code 使用记录——扫描原始会话数据,按主题分组汇总"我都做了什么",并从个人操作系统视角输出模式、风险与增删建议。当用户说 /recap、"看看我这几天做了什么"、"回顾一下我最近的会话"、"这两天我用 claude 干了啥"、"活动回顾" 时使用。
基于 SOC 职业分类
正在显示 SKILL.md
| 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=5 # Results per search
TOKEN_BUDGET=4000 # Context injection limit (per BP-039)
# Service endpoints
QDRANT_HOST=localhost
QDRANT_PORT=26350
EMBEDDING_HOST=localhost
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 statistics