# AgentLens Launch -- Twitter/X Thread

---

**Tweet 1 (Hook)**

Current agent observability tools tell you WHAT API calls your agent made.

They don't tell you WHY it picked tool A over tool B, or why it retried instead of escalating.

That's the gap I kept hitting. So I built something to fix it.

---

**Tweet 2 (What it does)**

AgentLens traces agent decisions, not just LLM calls.

It captures tool selection, routing, planning, retries, and escalation -- with the reasoning, alternatives considered, and confidence at each step.

Open source. MIT licensed. Built solo in 2 weeks.

#AI #OpenSource #Agents

---

**Tweet 3 (Code)**

Four lines to get started:

```
pip install vectry-agentlens

import agentlens
agentlens.init(api_key="key", endpoint="http://localhost:4200")
wrap_openai(openai.OpenAI())
```

Auto-instruments your OpenAI client. Then trace decisions as they happen.

---

**Tweet 4 (Features)**

What you get:

- Live Next.js dashboard with decision flows
- OpenAI auto-instrumentation via wrap_openai()
- 7 decision types: routing, planning, tool selection, retry, escalation, memory retrieval, custom
- Self-host with Docker Compose
- Python SDK on PyPI

#DevTools #LLM

---

**Tweet 5 (CTA)**

AgentLens is v0.1.0 -- early but functional. Rough edges exist.

Try the live demo: https://agentlens.vectry.tech
Repo: https://gitea.repi.fun/repi/agentlens
Install: pip install vectry-agentlens

Feedback welcome, especially on the decision model.

#OpenSource #AI #Agents
