by kurikomi-labs · Codex Skill · ★ 60
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komi-learn Continuous memory and self-improvement for coding agents. It learns how you work and recalls it automatically, with no commands. Works with Claude Code and Codex. It watches a session, distills durable lessons in the background (your style, your stack, fixes that worked), and loads the relevant ones at the start of the next session. No slash commands, nothing to save by hand. The idea is from Hermes Agent; this is my own take, generalized across hosts with an optional shared layer (the community pool, below). It's early. The core loop is built and CI-tested, but it hasn't been battle-tested across a lot of real sessions yet. Feedback and bug reports are welcome. Install runs a short interactive setup, then recall and background learning start in your next session. If you already use Claude Code you're already logged in. For scripts, takes the defaults.
| Stars | 60 |
| Forks | 0 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 72.2023446665854/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-09 |
| Created | 2026-05-29 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~36k |
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komi-learn is Continuous memory + self-improvement for AI agents. Learns how you work, recalls it automatically, no commands. Claude Code & Codex.. It is categorized as a Codex Skill with 60 GitHub stars.
komi-learn is primarily written in Python. It covers topics such as ai, ai-agents, ai-tools.
You can find installation instructions and usage details in the komi-learn GitHub repository at github.com/kurikomi-labs/komi-learn. The project has 60 stars and 0 forks, indicating an active community.
komi-learn is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to komi-learn on Agent Skills Hub include deepcontext-mcp, claudepro-directory, claude-historian-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.