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patkusch/README.md

I build the checks that stop AI agents doing what a bank would not allow, and I publish the experiments that failed as readily as the ones that worked.

Most of what I build sits underneath AI agents: keeping their work safe when they crash, checking that the notes they rely on are still true, and setting limits on what they may do without asking a person first.

Everything here is public, free to reuse (MIT unless the repo says otherwise), and runs from a fresh download.


Selected work

What it is Why it matters
apiary Keeps a team of AI agents working when one of them crashes When a worker stops, its job is handed to another worker. Each job is retried a limited number of times, and if it keeps failing it is held for a person to review.
acta A record of what an agent did that it cannot rewrite A logbook the driver can write in but cannot tear pages out of, with an honest list of which tricks it catches and which it cannot.
cresco A radar for which tech skills employers will want next Every prediction is written down with a date and later checked against what actually happened, misses published alongside hits. Six years of real job adverts behind it.
kontext Tells you which of your project notes are out of date Compares each note with the code it describes and when each last changed, so nobody trusts a note that stopped being true.
remit Rules for how much an AI agent may do on its own Asks how much damage one action could do before it is allowed unattended, mapped onto the rulebooks banks and EU regulators actually use.
assay Quick yes/no and pick-one answers from a small AI model on your own laptop, with a number for how sure it is An agent can ask "is this command dangerous?" in a fraction of a second and get an answer whose confidence can be checked. It says "not sure" when it should, and the scoreboard publishes the tests that showed no benefit.
aurora Finds where two approved documents contradict each other Two design documents, both signed off weeks apart, cannot both be true. It finds the clash in seconds and points at the exact lines.
hazlog The same, for hospital IT safety Catches contradictions that could harm a patient, and keeps patient data on site: only single words ever leave for the cloud model.

Also built

What it does
proctor Checks whether an AI agent picks the right tool, passes the right arguments, recovers from errors and stays in scope.
skillgate Checks an agent skill before you install it: what it can touch, what it claims to do, and whether it changed since you approved it.
agentsweep Shows what your AI agent tools have piled up on your disk and clears it safely. Nothing is deleted, it goes to a folder you can restore from.
cursus Turns a written process into a Visio flow chart, with the source sentence behind every box.
specto Watches a recorded expert walkthrough of a system and writes down what the system must do.
carryover Checks that every number, date, amount and name in a text survives translation.
dayline Writes up your day from your Claude Code sessions and git commits. Runs on your machine.

Pinned Loading

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    A regulatory-change investment-decision agent built on DataHub — discovers impact via lineage, costs ACT NOW / DEFER / MIN. COMPLIANCE, and writes the decision back into the graph.

    Python

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    Regulatory-change remediation copilot for financial services — the agent maps, groups and drafts; a human approves every cohort; every action is proven and audited. DORA demo.

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  4. remit remit Public

    An agentic skills framework for AI governance. Autonomy tiers, blast radius, and a diagnostic manual for agent failure modes — over EU AI Act, NIST AI RMF, ISO 42001 and DORA.

    Python