How ready are your agents for a bad day? Get your score

See everything your agents do.

Every run records itself — each model call with the exact context behind it, each tool execution with its output, each thing the agent tried and was not allowed to do.

nothing to instrumentthe exact promptwatch it livedenials on the record
tracing.agyn.dev/acme/runs/0586131e
agyn tracing Traces0586131eLUuser@agyn.dev
Finished15.04 sAug 10, 2026, 11:13 AM13,178 tokens
LLM Call
8/10/2026, 11:14:05 AM · 4.79 s · 13,178 tokens
Provider
openai
Model
gpt-5.6-terra
Context
View context history
User Aug 10, 11:14:03
thread: db7d6e91-6117-44f1-a6a6-4f43689709f5
from: 9c1c38a0-542f-437b-bf71-8a0c76dbf82a
Which suppliers drove the Q3 overspend?
Tool result Aug 10, 11:14:04
postgres_query → 1,204 rows
Reasoning
128 tokens
Output
Four suppliers account for 82% of the Q3 variance. Northwind and Contoso alone drove 61% of it, both through unbudgeted expedited freight.
Invoked tools
postgres_query

Nothing to instrument. Everything recorded.

Agent observability is usually a project — an SDK to wire in, a collector to run, dashboards to keep honest. Here there is nothing to add: the platform runs your agents, so it records them. Every run, every agent, from the first day.

Each run captures its model calls, tool executions, and timing — down to the token.

Tracing & cost · 4 features
AgentStatusTook
@finance-analystfinished15.04s
@contract-reviewrunning42s…
@supportfinished3.1s
@data-engineerfailed1.8s

Read the exact prompt behind any answer

Each model call stores the context that produced it — the instructions, the conversation, the tool results. “Why did it say that” is answered by reading, not by guessing.

Even compression is an event: when the conversation is summarized to fit the model, you can see what the agent stopped seeing.

Tracing & cost · 4 features
Context · llm call 2
View context history
systemYou are a finance analyst…
messageWhich suppliers drove the Q3 overspend?
tool_resultpostgres_query → 1,204 rows
summary…compressed from 14 earlier items

Watch it live. Stop it if you have to.

Runs stream as they happen — you watch tool calls land while the agent is still working, not in a post-mortem.

And when something looks wrong, terminate the run from the same screen. The kill switch is a button, not a support ticket.

Tracing & cost · 4 features
run · @finance-analyst · running · 2m 14sTerminate run
message received0.0s
llm call · context ▸ 14 items2.4s
tool · postgres_query312ms
tool · create_chartrunning…

Denials are on the record

When an agent tries something outside its rules — a domain that was never allowed — the attempt does not vanish into a timeout. It lands on the run as an event: what, where, when.

Your security team gets evidence, not anecdotes.

Egress · 3 features
tool · postgres_query312ms
egress denied
destination
pastebin.com
rule
no match → denied
recorded
11:14:07 · on the run
summarization148ms

See it on your own cluster.

Thirty minutes, your infrastructure, your stack. Or skip the call — it is one Helm release onto a cluster you already run.