understand-anything
claudeAI-powered codebase understanding — analyze, visualize, and explain any project
9 skills · 10 agents · hooks
A Claude Code plugin that's alive. Birth it, bond to it, build with it. It watches you work, learns your patterns, and grows.
Plugin homunculus from marketplace homunculus in humanplane/homunculus. Commands read from the repo's manifest — 1 month ago.
This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.
instinct-applySurfaces relevant instincts during work. Use when starting a task to check if any learned behaviors apply.
session-memoryMaintains awareness across sessions. Spawns observer agent on start, loads context, notifies of evolution opportunities.
/homunculus:evolveGrow new capabilities from clustered instincts
/homunculus:exportExport instincts for sharing
/homunculus:importImport instincts from others
/homunculus:initBirth or wake your homunculus
/homunculus:statusCheck in with your homunculus
observerBackground analyzer that runs on session start. Reads observations, creates instincts, detects clustering.
${CLAUDE_PLUGIN_ROOT}/scripts/observe.sh prompt
${CLAUDE_PLUGIN_ROOT}/scripts/observe.sh tool
${CLAUDE_PLUGIN_ROOT}/scripts/on_stop.sh
AI-powered codebase understanding — analyze, visualize, and explain any project
9 skills · 10 agents · hooks
Open-source AI job search that runs locally in your AI coding CLI: scan job portals, evaluate listings into a structured A-H report with a 1-5 score, tailor your CV, track applications
5 skills · hooks
Rewrite AI-sounding text so it reads like the writer without changing what it says.
1 skill
AI memory system — mine projects and conversations into a searchable palace. 47 MCP tools, auto-save hooks, guided setup.
3 skills · 6 commands · 1 MCP server · hooks
Perform AI code review on Git diffs — supports workspace changes, branch ranges, and single commits with concurrent per-file analysis, codebase search, and deep context-aware review.
2 commands
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
10 skills · 2 commands · 3 agents
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