# Gara

> A self-extending AI agent. When no skill fits a request, it researches the problem, writes and sandbox-tests a new skill, then installs it for next time.

- Role: Creator
- Period: 2026 – now
- Type: Open source
- Status: active
- Stack: TypeScript, LLM tool use, Sandboxed execution, Embeddings
- Source: https://github.com/kanephamphu/gara
- URL: https://phamphutai.com/projects/gara/

## The idea

Most agents have a fixed toolbox. When a request falls outside it, they either fail or improvise a one-off answer that is forgotten afterwards.

**Gara answers a request by finding a skill for it, or building one.** The next time a similar request arrives, retrieval hits and none of the building has to happen again.

## How it works

```
1. RETRIEVE   hit / adapt / miss
2. ADAPT      a skill is close: upgrade or fork it
3. TRIAGE     does this need a skill? split it into steps
4. CLARIFY    is the requirement clear? if not, ask
5. PLAN       run independent steps in parallel
6. FEDERATE   search the marketplace and install
7. RESEARCH   web search + fetch
8. SPECIFY    draft the spec and eval cases, audit them
9. AUTHOR     write the code
10. EVALUATE  run the evals in a sandbox
11. PROBE     attack it with input it never saw
12. CRITIQUE  review for over-reach and correctness
13. PROMOTE   install, embed, index
14. EXECUTE → VERIFY → SHARE (human-approved)
```

## What’s interesting

- **It improves what it has** instead of starting over: retrieval can hit, adapt an existing skill, or miss.
- **Every skill ships with its own eval suite**, so “it works” is checked, not assumed.
- **A critique step reviews each new skill for over-reach** before it is allowed to install.