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cortex-engine皮质引擎

Agent Skill

cortex-engine 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,245

周安装

374

GitHub Stars

1

下载量

2,902
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cortex-engine(皮质引擎)
来源仓库:https://github.com/idapixl/cortex-engine
安装命令:
openclaw skills install cortex-engine
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install cortex-engine

简介

AI 代理的持久认知记忆 - 通过传播激活、FSRS 调度等跨会话查询、记录、审查和巩固知识

SKILL.md

name
cortex-memory
version
1.0.0
description
Persistent cognitive memory for AI agents — query, record, review, and consolidate knowledge across sessions with spreading activation, FSRS scheduling, and NLI contradiction detection.
author
idapixl
tags
[memory, cognition, mcp, agents, knowledge-graph, spaced-repetition, code-review, fsrs]

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

76.48%
按下载量换算2,219

安全审计

VirusTotal

通过

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通过

Static analysis

通过

权限和风险

敏感数据

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安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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