memorix
Shared project memory for AI coding agents across sessions
All Skills in This Repository (22)
Pure Emerald Level Indicatorsmemorix-reasoning
Record and retrieve technical decision rationales linked to commit references.
memorix-troubleshooting
Diagnose and resolve Memorix MCP, setup, and integration issues.
memorix-memory
Centralize project memory access for AI coding agents via YAML configuration.
memorix-sessions
Manage session states and contexts for AI coding agents.
memorix-git-memory
Search and inspect Git commit history to retrieve project memory.
memorix-orchestrate
Coordinate subagent tasks, handoffs, messages, and file locks in AI coding environments.
memorix-mini-skills
Convert project knowledge into reusable mini-skills for AI agents.
memorix
Manage shared project memory and session context for AI coding agents.
missing-description
Skill without a description field.
different-name
Validate that a skill's directory name matches its SKILL.md name.
multiline-description
Normalize multiline YAML descriptions into single-line format.
root-skill-preferred
Prioritize root skill execution before nested skills in hierarchies.
Frequently Asked Questions
FAQPage SchemaHow to install Memorix?โผ
Run `npx skills add AVIDS2/memorix --all -g -y` in your terminal to install all Memorix skills globally for your AI agent.
How to give AI coding agents persistent memory?โผ
Memorix stores decisions, bug fixes, and project context in a local database tied to your Git project, so any agent session can search and recall it later.
Does Memorix work with Claude Code and Cursor?โผ
Yes. Memorix connects to Claude Code, Codex, Cursor, Copilot, Gemini CLI, Windsurf, and other agents through MCP, plugins, hooks, and skills.
Can Memorix remember why a design decision was made?โผ
Yes. Its reasoning memory stores the rationale, alternatives, and trade-offs behind decisions, and can link them to the exact Git commits as evidence.
Does Memorix need an API key or cloud account?โผ
No. Memorix is local-first and works with built-in full-text search out of the box; LLM-backed embeddings are optional.
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