keshrath

Agent Knowledge — AI skill for Claude Code

AI community

Cross-session memory and recall for AI agents — git-synced knowledge base, hybrid semantic+TF-IDF search, auto-distillation with secrets scrubbing.

How to install Agent Knowledge

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

What Agent Knowledge does

Cross-session memory and recall for AI agents — git-synced knowledge base, hybrid semantic+TF-IDF search, auto-distillation with secrets scrubbing.

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README

agent-knowledge

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) [![Node >= 20](https://img.shields.io/badge/Node-%3E%3D%2020-brightgreen.svg)](https://nodejs.org) [![Tests: 604 passing](https://img.shields.io/badge/Tests-604%20passing-brightgreen.svg)]() [![MCP Tools: 6](https://img.shields.io/badge/MCP%20Tools-6-blueviolet.svg)]() [![LongMemEval R@5: 98.8%](https://img.shields.io/badge/LongMemEval%20R%405-98.8%25-brightgreen.svg)]()

**Cross-session memory and recall for AI coding assistants** -- works with Claude Code, Cursor, OpenCode, Cline, Continue.dev, and Aider out of the box. Git-synced knowledge base, hybrid semantic+TF-IDF search, auto-distillation with secrets scrubbing.

**Benchmark:** **R@5 = 97.2% (sparse) / 98.8% (hybrid)** on `longmemeval_s` and **86.0% (sparse) / 88.4% (hybrid)** on the harder `longmemeval_m` split — the public LongMemEval academic benchmark (Wu et al. 2024, ICLR 2025), full 500 questions per split, no LLM, no API key, runs entirely offline. **+8.6pp to +13.2pp R@5 over the paper's official `flat-bm25` baseline** in apples-to-apples reproduction. Full per-category table, reproduction instructions, and paper-comparison details in [`bench/README.md`](bench/README.md).

In Claude Code, the agent-knowledge plugin adds the `/knowledge` pane: the knowledge base beside the conversation. How it works, with pictures: [the user manual](docs/USER-MANUAL.md#4-the-knowledge-pane).

![The /knowledge pane: open it, open an entry, follow a link](docs/images/manual/hero.gif)

Why

AI coding sessions are ephemeral. When a session ends, everything it learned -- architecture decisions, debugging insights, project context -- is gone. The next session starts from scratch.

**agent-knowledge** solves this with two complementary systems:

Knowledge Base -- a git-synced markdown vault of structured entries (decisions, workflows, project context) that persists across sessions and machines.
Session Search --