raj742133

Evermind — Development skill for Claude Code

Development community

Claude Code skill: automatic memory across /clear, context refresh handoffs, and a live local dashboard.

How to install Evermind

This entry records only its repository, not the path inside it, so there is no exact command to give. Open raj742133/evermind and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Evermind does

Claude Code skill: automatic memory across /clear, context refresh handoffs, and a live local dashboard.

Alternatives in Development

  • Resume Work From A Handoff Document — You are tasked with resuming work from a handoff document through an interactive process 10k ★
  • Claude Supermemory — Persistent memory across sessions and projects using Supermemory 2.3k ★
  • Clear Code — See your claude code logs in clear details in your dashboard 2.1k ★

README

evermind

**A Claude Code skill that remembers everything and keeps your context small.**

Automatic memory across `/clear`, handoff-and-refresh before context bloat, and a live local dashboard.

![python](https://img.shields.io/badge/python-3.9%2B-3776ab?style=flat-square) ![tests](https://img.shields.io/badge/tests-54%20passing-2e8b57?style=flat-square) ![license](https://img.shields.io/badge/license-MIT-lightgrey?style=flat-square) ![local](https://img.shields.io/badge/runs-100%25%20local-d9532c?style=flat-square)

evermind dashboard, light theme

Why

Every request in Claude Code re-reads the whole conversation, so usage grows with context size. A long chat gets expensive and slow, and `/clear` throws away what you learned.

evermind fixes both:

  • It restarts from a small context before the chat gets heavy: writes a short handoff, then you type /clear.
  • It remembers everything from the moment it is installed: prompts, replies and tool calls are captured, durable facts are extracted, and relevant older memory is injected back before each prompt.
  • It shows you what is happening, live, in a minimalist dashboard that opens by itself.

In our own measurements on real sessions, this cut estimated usage by roughly 30 to 40 percent on long chats.

How it works

flowchart LR
    A[You chat] --> B[Hook: capture
prompts, replies, tools] B --> C[(Local memory
facts + history)] A --> D{Context over 150K
or cache cold?} D -- yes --> E[Handoff
Goal / State / Next] E --> F[You type /clear] F --> G[Fresh session
digest + handoff injected] C --> G C -- relevant facts --> H[Recall hook
before each prompt] H --> A
Piece What it does
refresh_check.py Hook. Triggers a refresh when context passes 150K tokens, or when the cache went cold over 60K+.
handoff_check.py Validates