Session Analyzer

It takes agents to control agents.

Guardrails stop what you can name in advance. The Session Analyzer reads the rest: an agent that scores every action for intent and syntax, before it executes.

hoop.dev sidecarlistening
LLM Analysis (in-transit)
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#compliance-alerts

Escalated to @sarah (compliance). AI analysis attached.
Session context: 4 PII queries in 24h from same user.

The gap

You cannot write a rule for every dangerous statement.

A deny list catches what you thought of. DROP, TRUNCATE, DELETE without a WHERE. Those are the easy ones, and they are worth blocking outright.

The harder case is a statement that breaks no rule. Every query below is permitted. Read in sequence, they are an extraction. Nothing in a list of forbidden operations sees that.

How it works

A score on every action, while it is still in the sidecar.

The analyzer runs on the statement your agent just sent, in the same pass as the deterministic rules. It returns a risk score. The score decides what happens next.

Intent and syntax, together

Syntax alone says a statement is well formed. Intent asks what it is for. A SELECT with no WHERE on a table of ten rows and the same statement on a table of ten million are different acts.

Before it executes

The score comes back while the statement is still in the sidecar. Nothing has reached your database yet, so the outcome is still a choice.

One of three outcomes

The score decides: pass, block, or route to a human. The same three outcomes every other control produces, so a scored action and a rule-matched action are handled the same way downstream.

Your model, your key

Point the analyzer at the provider you already cleared. Your API key, your data policies, your region.

Why an agent

Not smarter than your agent. Just as fast, and narrower.

The Session Analyzer does not understand your business. It is not trying to. It has one job and a few hundred milliseconds to do it: read this statement, judge what it is for, return a score.

A static rule cannot judge intent.

It matches a pattern you wrote in advance. That is why it is reliable, and that is also its ceiling.

A human cannot review at machine speed.

Your agent issues the next statement in milliseconds. A person reading a queue is already behind.

So the control has to be an agent too.

One that moves at the speed of the thing it watches, with a single job: read every statement live and stop the dangerous one before it lands.

Point it at a model and it starts scoring.

One key in the config file, and every action your agents take gets read before it runs. Free and open source under MIT.

Ask AI how the hoop.dev Session Analyzer works