emulo
Active·★ 197·MIT·Updated 2026-07-20
★ Trending★ Hidden Gem
Emulo is an open-source tool that mines your past AI agent coding sessions (e.g., Claude Code, Codex) to build a private working profile. This profile, containing unwritten rules and preferences, allows agents to understand your unique workflow and act more like you before every task.
emulo is currently grouped under Memory & Context, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Mines implicit user behavior from raw AI agent session logs and Tailoring AI agent responses and coding style to user preferences. The listed license is MIT, which is useful when adoption constraints matter. It also shows measurable community traction with 197 GitHub stars.
#AI Agent Personalization#LLM Context Management#Behavioral Profiling#Code Agent Workflow#Session Log Analysis#Privacy-preserving#Developer Tooling#Agent Memory
01
Features
01Mines implicit user behavior from raw AI agent session logs
02Generates a personalized working profile for agents to read
03Supports multiple AI agent platforms and LLMs (e.g., Claude, Codex, Gemini)
04Processes data locally with built-in redaction for privacy
02
Why choose it
+Mines implicit user behavior from raw AI agent session logs
+Tailoring AI agent responses and coding style to user preferences
+Covers 7 supported environments or platforms, which is helpful for broader deployment needs.
+Ships with a public repository and a MIT license, which makes adoption and review easier.
03
Trade-offs
!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.
04
Compatibility
Python
Runtime
Verified via docs
Claude Code
Agent
Verified via docs
Codex
Agent
Verified via docs
Cursor
Agent
Verified via docs
Gemini
Agent
Verified via docs
OpenCode
Agent
Verified via docs
05
Quick start
1
$ npx skills add ohad6k/emulo@emulo
06
Use cases
↳Tailoring AI agent responses and coding style to user preferences
↳Reducing repetitive instructions by providing agents with implicit context
↳Enhancing agent decision-making by learning from past user interactions
↳Integrating a personalized context layer into various agent workflows
07
How it compares
≈emulo sits in the Memory & Context category, so it makes more sense to evaluate it alongside tools like headroom instead of in isolation.
≈If your main need is closer to "Tailoring AI agent responses and coding style to user preferences", that use case is a better lens for comparison than broad feature checklists alone.
≈emulo uses a MIT license, and community traction are both easier to judge in category context.
08
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metatron★ 20
Metatron is a self-hosted system that captures a codebase's real implementation decisions — preferred patterns, rejected approaches, edge cases, internal conventions — as structured priors, and serves them to coding agents over MCP (Model Context Protocol). The goal: an agent writes code like a senior engineer who already knows the codebase
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