← 返回
AI智能 中文

Cortex Engine

Persistent cognitive memory for AI agents — query, record, review, and consolidate knowledge across sessions with spreading activation, FSRS scheduling, and...
为AI智能体提供持久化认知记忆——支持跨会话的知识查询、记录、回顾与整合,具备扩散激活、FSRS间隔重复调度等功能。
idapixl
AI智能 clawhub v1.0.1 1 版本 100000 Key: 无需
★ 1
Stars
📥 577
下载
💾 9
安装
1
版本
#agents#code-review#cognition#knowledge-graph#latest#mcp#memory#spaced-repetition

概述

Cortex Memory

Persistent memory engine for AI agents. Knowledge survives across sessions — recall what you learned last week, track evolving beliefs, detect contradictions, and build a knowledge graph over time.

Source: github.com/Fozikio/cortex-engine (MIT) | npm

Prerequisites

This skill requires cortex-engine running as an MCP server. Install it separately before using this skill:

npm install cortex-engine@0.5.1
# Integrity: sha512-8oIL8KenrdTdACAMSM/iqyrxx04yFE/3IfHx1dTF2439ljXhSCvULcNF5V10tH8UK7P/zuwmx3RuNynvjGi4kg==

Then initialize and start:

npx cortex-engine@0.5.1 fozikio init my-agent
npx cortex-engine@0.5.1  # starts MCP server

Runs locally with SQLite + Ollama. No cloud accounts needed. The skill instructions below are read-only — they teach your agent how to use cortex tools, they don't execute anything.

Core Loop

Read before you write. Always check what you already know before adding more.

Search

query("authentication architecture decisions")

Be specific. query("JWT token expiry policy") beats query("auth"). Results include relevance scores and connected concepts.

Explore around a result:

neighbors(memory_id)

Record

Facts — things you confirmed:

observe("The API rate limits at 1000 req/min per API key, not per user")

Questions — unresolved:

wonder("Why does the sync daemon stall after 300k seconds?")

Hypotheses — unconfirmed ideas:

speculate("Connection pooling might fix the timeout issues")

Update beliefs

believe(concept_id, "Revised understanding based on new evidence", "reason")

Track work across sessions

ops_append("Finished auth refactor, tests passing", project="api-v2")
ops_query(project="api-v2")  # pick up where you left off

Memory-Grounded Reviews

Review code or designs by comparing against accumulated knowledge:

  1. Ground: query("the domain being reviewed") — load past decisions and patterns
  2. Compare: Does the work align with or diverge from established patterns?
  3. Record: observe() new patterns, wonder() about unclear choices, believe() updated understanding
  4. Output:
## Review — Grounded in Memory

### Aligned with known patterns
- [matches cortex context]

### Divergences
- [what differs, intentional or accidental]

### New patterns to capture
- [novel approaches worth observing]

Session Pattern

  1. Start: query() the topic you're working on
  2. During: observe() facts, wonder() questions as they come up
  3. End: ops_append() what you did and what's unfinished
  4. Periodically: dream() to consolidate memories (compress, abstract, prune)

Available Tools

CategoryTools
-----------------
Readquery, recall, predict, validate, neighbors, wander
Writeobserve, wonder, speculate, believe, reflect, digest
Opsops_append, ops_query, ops_update
Systemstats, dream

版本历史

共 1 个版本

  • v1.0.1 当前
    2026-03-31 15:40 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

ai-intelligence

Self-Improving + Proactive Agent

ivangdavila
自我反思+自我批评+自我学习+自组织记忆。智能体评估自身工作、发现错误并持续改进。
★ 1,349 📥 317,699
ai-intelligence

ontology

oswalpalash
类型化知识图谱,用于结构化智能体记忆与可组合技能。支持创建/查询实体(人员、项目、任务、事件、文档)及关联...
★ 709 📥 243,529
data-analysis

Cortex Query (Deprecated)

idapixl
[已弃用] 此技能已合并到cortex-engine,请改用clawhub.ai/idapixl/cortex-engine。
★ 0 📥 525