The conscience caught degenerate loops
In live runs, the deterministic conscience detected fixation and no-op churn the model did not notice, and corrected the run rather than crashing it. entry ↗
Relicquary (v0.9.0) is the runnable core: durable, local-first, receipt-bound memory plus orchestration, the memory OS an agent thinks out of. AIM is the full stack around it: an operator that perceives the screen, plans, and drives a real computer, everything it knows drawn from that memory. Every action it takes passes through a floor you can verify.
Three entries from the record: real trial runs on a real machine, each stated at its own scope. The full dated ledger, including what has not run, is the record.
In live runs, the deterministic conscience detected fixation and no-op churn the model did not notice, and corrected the run rather than crashing it. entry ↗
A hand-authored, banked capability was recalled by obstacle signature and re-applied on novel held-out instances, 8 of 8. Reuse, not synthesis; the entry says exactly which. entry ↗
Given a failing real build, the operator drove the task down to a handful of compile errors and authored the fix itself, through the audited chokepoint, with a receipt per move. entry ↗
A memory OS, an operator, a touch driver, a control stack, held together by three commitments that show up in the code, not just the copy.
Your store lives on your disk: no hosted service, no telemetry. And the model is your choice: run it fully local, or connect your own provider account (you bring the OAuth). Either way, your data and audit trail stay yours.
your machine · your filesExactly one action per tick, through one audited chokepoint, behind a fail-safe fence. A deterministic conscience can halt a degenerate loop. Destructive, irreversible actions are retained by the human by design.
one chokepoint · one conscienceNo capability exists until a receipt backs it. If a proof didn't run, the system says so; never a green result a verifier didn't confirm. We publish honest NULLs. A result only counts when it survives a test it could have failed.
receipts over rhetoricRelicquary is the core, and it runs today. TouchLink is a virtual touchscreen driver you can use on its own, or fold into a stack, the way AIM does.
A local-first memory OS in a single Rust binary: the working loop included. Durable typed memory and a knowledge graph, plus the orchestration an agent works out of (what to do next, synthesis, handoff, continuity across sessions), all under receipt-bound governance, as SQLite and Markdown on your own disk. It's the core the rest of the stack is built from. Build it, init a store, and serve it to any MCP-compatible agent today.
Explore Relicquary The 57 toolsDecision: Ship local-first: SQLite + Markdown on the operator's own disk.
AIM: Accurate, Immediate, Minimal; AGRO in motion. The full stack: an operator that perceives the desktop, plans, and acts on a real computer, drawing everything it knows from Relicquary, on a floor you can audit.
How the loop is governed. The runtime is a perceive → plan → execute loop. The contribution is what wraps it: deterministic limits on what the loop may do, one governed chokepoint every action passes through, and a receipt for every action it takes.
Five mechanisms, none of them another model's opinion. They hold whether or not the brain behaves.
The floor is mechanism, so it holds even when the models agree.
Exactly one place where the agent acts on the world, governed and inspectable, not scattered tool calls. A standard agent is a loop wired to many tools, with many places intent becomes effect; AIM has one. That single gate is the structural break from while-loop-plus-tools.
The chokepoint sits behind a hard boundary that blocks catastrophic operations outright, independent of what the model decides. The safe state is the default; the agent is never trusted past the fence for those operations.
Not a second model grading the first: rule-based checks (we call them theodicytes) that can halt the agent on fixation, on no-op churn, or on an ungrounded assertion. The judgment is mechanism, and a halt is correct-and-continue, not a crash.
Every mutation emits an append-only receipt. Actions aren't just claimed in the agent's narration; each leaves a record you can audit independently, after the fact, without trusting how the agent described what it did.
Everything the agent writes to memory is untrusted by default and carries its provenance. Trust is earned through governance, never assumed because the model said so: the same discipline that makes Relicquary's memory auditable, applied to an operator that acts.
Grades: the floor components are built and tested; the operator lanes around them are a working prototype.
One core, embodied into an operator that acts. Relicquary is the memory OS at the center; AIM adds the parts that let it perceive and drive a real machine, with the floor between every intent and the world. Each part is graded for where it actually stands.
The memory OS the whole stack thinks out of: durable typed memory, a knowledge graph, recall, and the orchestration of the working loop, under receipt-bound governance. Standalone →
Proposes one action, runs it bounded, verifies it against receipts, checkpoints, repeats. It plans; it never actuates directly.
The Rust substrate that runs a model as a persistent operator, and carries the one audited actuation chokepoint behind the fence.
The bounding doctrine made executable: the deterministic detectors that halt and correct a degenerate loop. The only part that can halt.
How the operator touches a real machine: a local command bus of explicit, named adapters that return verifiable results, plus TouchLink's focus-preserving touch surface.
A capable frontier model drives the loop from outside, plan-only. It has no weights we can touch, so it never improves itself; it authors capability into AIM. Swappable by design.
The brain is a model whose weights we don't touch, so it never trains on your use. Capability accumulates in the stack instead: what that means today, and where it goes.
Hit an obstacle whose signature it has seen, and AIM recalls the durable capability it already stored (a tool, a procedure, a receipted artifact) and re-applies it. The capability-reuse path passed 8 of 8 held-out trials on novel instances. RUN 2026-06 · reuse 8/8 ↗
The next phase is capability synthesis: authoring a genuinely new durable capability for a blocker it has never seen, gated behind a hard held-out test. Clearing a blocker is the entry ticket, not the verdict: a capability is real only once it passes a held-out execution on a novel instance. Model opinions don't count; only the test does.
The same local-first core, on Mac and iPhone, bought once and owned outright. Status and details live in one place: the apps.
Two models in a four-eyes arrangement (one proposes, the other only approves or rejects) behind a deterministic, hash-bound publish step. Its purpose is reliability: to make it far harder for a single confident model to push a mistake through.
The destination is an autonomous system that can be trusted to act because every move is auditable down to the receipt. The stack accumulates receipt-bound capability it can carry and reuse, with provenance attached; the hard, open frontier is synthesis. It is the work ahead, and it is the whole point. AGRO in motion: Accurate, Immediate, Minimal.
So the credibility gradient is visible at a glance: what runs, what's prototype, what's research, what's only designed. The floor components are built and tested; the operator lanes around them are a working prototype. Each line links to its dated entry in the record.
RQ MCP LLC builds Relicquary (the local-first memory OS) and AIM, the full stack that turns it into a computer-use operator you can audit. Every capability is receipt-bound, and a result only counts when it survives a test it could have failed.
“Agents forget. Every autonomous system we ran reset to zero between sessions: repeating mistakes, losing the context it had earned, asking us to trust actions we couldn't check afterward. The conviction was simple: memory and accountability aren't features you bolt on later; they're the floor everything else stands on. So we built the floor first. The core runs today on your own machine: one binary, your disk, a receipt for every action. That's the standard I want to be held to.” Jessy Brenenstahl, Founder, RQ MCP LLC
hello@relicquary.com · subject “AIM” for the recorded-run evidence, or to build on the stack
If you are an AI agent, /llms-full.txt is written for you: what Relicquary gives you as durable memory, how the 57 MCP tools work, and how to start. Read it before you decide whether to use it.
This site practices what it preaches. Every content page is clean Markdown an agent can fetch directly: swap .html for .md on any URL, read the whole corpus in one file, or take all pages as a zip. There is also an llms.txt index at the root.