neuron-explorer
Qwen3.5‑4B 전용 조향형 뉴런 탐색기, 모든 MLP 뉴런을 밀어 결과를 보관·탐색
팀이 공유하는 Git 기반 지식 베이스, 레포에 구축돼 코드처럼 검토·버전 관리, 별도 인프라 필요 없음
A team-shared, git-native knowledge base for AI coding sessions. Built up in your repo, reviewed and versioned like code, with no extra infrastructure to run.
개발 도구JavaScript · TypeScriptGitHub @e0ipso온라인운영자 미확인
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Knowledge base for AI projects.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
A team-shared, git-native knowledge base for AI coding sessions.
Built up in your repo, reviewed and versioned like code, with no extra infrastructure to run.
Coding assistants forget everything between sessions. Kenkeep salvages the gold nuggets from your past conversations and discards the rest, so the detail you explained two weeks ago is there the next time the assistant needs it.README 전문 보기 ↗Coding assistants forget everything between sessions. Kenkeep salvages the gold nuggets from your past conversations and discards the rest, so the detail you explained two weeks ago is there the next time the assistant needs it.
Kenkeep is a team-shared, git-native knowledge base for AI coding assistants. Conventions, gotchas, module names, and the reasons behind decisions get captured from your sessions, curated by a human, committed to the repo, and injected back into every future session.
One markdown file per fact, accumulated from real coding sessions and stored in your repo. It travels with git pull, so every teammate works from the same conventions instead of rediscovering them alone. The nodes/ tree is an Open Knowledge Format bundle any OKF tool can read.
Nothing reaches the knowledge base without a human approving it. Every addition is an ordinary git diff you review in a commit or PR, with the full history there to blame or revert.
No daemons, services, databases, or vector stores. Kenkeep is Node and git. Nothing to provision, host, keep alive, or secure.
It runs inside the assistant you already pay for: Claude Code, Codex, Cursor, OpenCode, or Copilot. There is no separate key to obtain, store, or rotate.
/kk-curate and the assistant drafts one note per durable fact, then walks you through any contradiction with a note you already have.git diff and commit the ones you want.A note curate can't place still doesn't get stuck: it lands at the nodes/ root, and the next npx kenkeep init --upgrade files it from its own edges and tags, or removes it when it matches nothing in the tree. npx kenkeep node sweep does the same on demand between upgrades. Both leave the result uncommitted, so you accept it with git commit and reject it with git restore.
Full walkthrough: How it works.
npx kenkeep init --harnesses claude
npx kenkeep doctor
Swap claude for codex, cursor, opencode, or copilot, or pass a comma-separated list. Per-harness details, including where GitHub Copilot CLI keeps its hooks and skills, are in Installation.
Then code as usual. When the assistant nudges you, run /kk-curate in your session. New notes land under .ai/kenkeep/nodes/. Review them with git diff and commit the ones you want to keep.
If your repo already has READMEs, ADRs, or module docs, seed the knowledge base from them. Inside a session:
/kk-bootstrap
The scan starts at the repo root and honors .kkignore, which init creates with gitignore syntax. Review the resulting notes with git diff and commit the ones you want.
Mid-session, mention /kk-add and the assistant records the point you just made:
No, you got that wrong.
This project aims to maximize code
re-use, instead of duplication. Adapt
and extend the abstractions to fit
this use case. Also, /kk-add this.
A pack is a reviewed nodes/ tree published for a framework, platform, or shared domain. Import one and it lands as a single isolated branch in your own knowledge base:
npx kenkeep pack import e0ipso/kenkeep-pack-drupal
npx kenkeep pack import https://github.com/e0ipso/kenkeep-pack-drupal --as drupal
Import is deterministic and never calls an LLM. A pack whose note ids collide with yours is rejected so you can decide. Import requires .ai/kenkeep/ and AGENTS.md to be committed, so git can undo a failed run. Full guide: Knowledge packs.
Full documentation: https://kenkeep.canpicasoft.com
Working on the package itself? See CONTRIBUTING.md.