A personal knowledge base that learns, grows, and works alongside you in Claude.
npx claudepluginhub farzadshbfn/knowledge-pluginPersonal knowledge base management — learn, find, compact, mint, view, and monitor your knowledge.
farzadshbfn
You read an article, learn something new, move on. A month later you've forgotten half of it. Claude forgot all of it the moment the conversation ended.
This plugin gives you a shared knowledge base. When you learn something, Claude learns it too, checks it against what you both already know, and keeps it around for next time.
Source code and tests: knowledge-skills.
/plugin marketplace add farzadshbfn/knowledge-plugin
/plugin install kb@farzadshbfn
claude --plugin-dir /path/to/knowledge-plugin
/kb-bootstrap
Creates the config and directory structure. Run once per project.
Tech moves fast. New frameworks, new conventions, a constant stream of articles and release notes. Even when you do read something useful, it's gone from your head a month later.
LLMs can help, but they forget everything between conversations and their training data lags behind. Context windows are expensive and finite. You end up re-explaining the same things, re-looking-up the same references, losing the insights you already earned.
This plugin fills that hole:
| Skill | Purpose |
|---|---|
/kb-learn | Learn from articles, research topics, fix KB errors |
/kb-find | Look up existing knowledge with progressive, token-efficient loading |
/kb-compact | Split oversized notes, unify terminology, fix indexes |
/kb-mint | Convert KB topics into skills, package as distributable plugins |
/kb-view | Local web renderer with fuzzy search, markdown rendering, and knowledge graph |
/kb-monitor | Track access patterns, surface skill candidates, check skill health |
/kb-bootstrap | First-time setup, run once per project |
/kb-learn runs a multi-agent pipeline:
--challenge)/kb-learn article <url> # Extract and assess claims from an article
/kb-learn topic "raft consensus" # Research a topic, fill gaps in your KB
/kb-learn fix "X actually works like Y" # Correct a mistake
After learning, ask Claude to summarize what it found, explain trade-offs, or compare against what you already knew.
/kb-find progressively loads only what's relevant:
Tier 1 → Topic tree (names + descriptions only)
Tier 2 → Frontmatter scan (first 15 lines of candidates)
Tier 3 → TOC + targeted sections
Tier 4 → Full note read (only when necessary)
A lookup in a 10,000-line KB might only load 50 lines into context. Challenge mode (--challenge) looks for contradicting evidence.
/kb-view starts a local HTTP server with a single-page app:
/kb-compact keeps your KB healthy as it grows. It splits large notes, merges duplicates, unifies terminology, and rebuilds indexes. --deep mode traverses the entire KB bottom-up.
Access patterns are tracked across conversations. When topics keep coming back, they're flagged as skill candidates. These are topics mature enough to be a dedicated skill rather than a loose collection of notes.
/kb-mint converts those candidates into standalone skills or packaged plugins for distribution. The pipeline: raw notes, then structured knowledge, then reusable skill, then distributable plugin.
A single centralized KB works until you're juggling multiple domains, then you're loading irrelevant context every time.
Multi-KB lets you co-locate knowledge with the domain it serves: