/loop — Iterative Improvement

What It Does

/loop runs the Algorithm as a loop — multiple full Algorithm cycles on the same target, each iteration building on the last. By default a human reviews and redirects between iterations. Unlike /optimize (an autonomous mutation loop), /loop runs full Algorithm passes with that human review in the seam.

The Problem

Some work doesn't finish in one pass. A skill, a prompt, a diagram, a piece of writing gets meaningfully better each time you run a full cycle on it — but only if each cycle remembers what the last one learned and what it already tried. Run the cycles by hand and you lose that thread: you re-explore dead ends, forget which approaches got rejected, and have no record of whether the score actually moved. /loop carries ISC criteria and a dead-ends ledger across iterations so each pass starts from where the last one ended.

How It Works

Each iteration is a full Algorithm cycle (OBSERVE → LEARN). The LEARN phase of one cycle feeds the OBSERVE phase of the next, the ISA tracks iteration count and cumulative improvements, and a human approves or redirects between iterations unless autoresearch mode is enabled.

Invocation