Skip to the content

How it works

How it decides

A funnel that goes from cheap to careful. Most things are settled by plain rules in a blink. Only what’s worth a second opinion goes to the model, and the final word always stays in code.

#The funnel

  1. Inventory

    Find everything aboard, in one pass, with no setup.

  2. Memory by content

    Every item is fingerprinted. Anything whose bytes haven’t changed since last time is skipped, and anything you’ve cleared stays cleared until its code changes.

  3. Facts from the syntax tree

    A pass over the code’s syntax tree finds what it can actually do. Each fact keeps its file and line.

  4. Combinations, in code

    Some pairs of facts mean more than their parts. Only these can hold the ship.

  5. Claim against behaviour, on your laptop

    For anything worth a second opinion, the local model compares the item’s own description with its short list of facts.

  6. Severity stays in code

    The model can nudge a single fact, never a combination.

  7. The morning report

    One verdict, a short queue, the real code, and an honest map of what couldn’t be read.

#The facts it looks for

Facts are things the code can do, read from its structure, not guessed from its words:

None of these is bad on its own. A downloader makes network calls. That’s why most facts are only noted.

#What can hold the ship

Only combinations found in code:

#The four levels

LevelMeansWho can set it
HeldDoes more than it says. Look before you ship.Only a combination found in code.
Worth a glanceA fact the description doesn’t call for.The rules, or the model raising a single fact.
NotedA power you’d expect from it.The rules, or the model lowering a single fact.
FineNothing found.The rules.

#What the model does, and doesn’t

The model sees the item’s own description, marked clearly as untrusted data, and the short list of facts. It says, fact by fact, whether the description calls for it, and it must cite fact ids that exist. It never sees your other code, and it never decides alone.

This is what makes prompt injection pointless here. A README that tells AI scanners to approve everything can sway the model, and in testing it sometimes did. But the hold comes from code, and the model can’t touch it.

The model isn’t repeatable bit for bit: between two runs on the same project it moved 4 package verdicts by one step. Rules-only verdicts didn’t change at all.

Suggest a change to this page

Esc