Hicortex — AI skill for Claude Code
Self-learning memory for AI agents — experience captured automatically, distilled into lessons overnight, shared across your whole fleet.
How to install Hicortex
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open gamaze-labs/hicortex and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Hicortex does
Self-learning memory for AI agents — experience captured automatically, distilled into lessons overnight, shared across your whole fleet. Works with Hermes, OpenClaw, Claude Code, and Pi.
Alternatives in AI
- Iai Personal Memory Engine — A cyber brain for your AI 866 ★
- OpenMobius Skill — ICT/SMC trading-knowledge skill for AI coding agents (Claude Code / Codex / OpenClaw / Hermes) 660 ★
- Metaharness — 🛠️ The meta-harness for AI agents — scaffold your own focused, branded agent harness with its own npx CLI, MC 616 ★
README
Hicortex
[](https://www.npmjs.com/package/@gamaze/hicortex) [](https://www.npmjs.com/package/@gamaze/hicortex) [](LICENSE) [](https://nodejs.org)
**Memory that shows up before your agent asks.** One memory across every agent, every project, every machine — they stop assuming and start knowing.
- One brain, every harness — Claude Code, Hermes, OpenClaw, Pi, OpenCode, and any MCP-compatible agent share the same memory.
- Pushed, not pulled — a compact recall index is injected on every prompt, so the decisions, corrections, and context an agent needs are already in front of it. No re-explaining, no copy-paste, nothing to maintain. Zero LLM calls per turn — no API cost or rate-limit hit from recall.
- Consolidates overnight — each night it reads the day's sessions, distills what matters, and turns it into Learnings, links, and a knowledge graph.
- Local-first — raw sessions never leave the machine; only distilled memory is stored.
Install
npx @gamaze/hicortex initAuto-detects your environment, configures one LLM (Ollama, the Claude CLI, or an API key), installs a local daemon (launchd on macOS, systemd on Linux), and registers MCP tools with Claude Code.
For multi-machine setups, point thin clients at a shared server — no local DB or LLM on the clients:
npx @gamaze/hicortex init --server https://your-server.example.com`init` auto-detects the other harnesses and installs their clients: a Pi extension (`~/.pi/agent/extensions/hicortex.ts` — pushed recall, identity + lessons, the nine tools; or copy `pi-extension/hicortex/index.ts` there ma
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