AI Agent Loop Builder
Pick your task. Get a complete starter loop kit: a verifier checklist, a stopping condition, a budget cap, doom-loop tripwires, and a copy-paste loop prompt.
Built on the methodology in our full loop engineering guide: the verifier is the bottleneck, not the model.
How it works
Pick your task type
Refactor, bug fix, content, data pipeline, research, UI, tests, or ops.
Set cadence and risk
One-shot or scheduled; how bad is a wrong run that ships?
Copy your loop kit
Verifier, stop condition, budget cap, tripwires, and the assembled loop prompt.
The 4 Parts of a Loop That Doesn't Doom-Loop
Every kit this tool generates covers the four things an unattended agent loop must have pinned before it runs.
Verifier checklist
Measurable passes that define "done" - build green, tests passing, schema valid, diff in scope. The verifier decides, not the model's own judgment.
Stopping condition
All checks green, or a hard iteration cap - then summarize and stop. The bound is what makes it a loop instead of a runaway.
Budget cap
A hard per-run spend cap (and a monthly ceiling for recurring loops), sized to risk. Start tight; raise it only with run data.
Doom-loop tripwires
Immediate-stop conditions per task type: same check failing 3 rounds, a growing diff, a deleted test, a fabricated source.
Where this methodology comes from
Every kit follows the discipline laid out in our full loop engineering guide: a loop is a generator wired to a verifier, and the verifier is the bottleneck. Define "done" in measurable terms before writing a single instruction, pin the passes up front, choose closed over open unless you've budgeted for novelty, and give every loop a bound so a bad run can't spin forever.
A template starts the loop. The course makes it ship.
The Loop Engineering course takes you from "you are the for loop" to a loop that wakes on schedule, pulls the top task off your backlog, ships a PR behind quality gates, and reports back - with a copy-paste practice on your own repo every lesson.
Take the Loop Engineering courseFAQ
What is a verifier in an AI agent loop?
The half of the loop that judges whether the work meets the bar. The generator (the model) produces; the verifier decides whether it ships, retries, or stops. Because the generator runs cheaply over and over, the verifier is the bottleneck - a good one is a checklist of measurable passes, not the model grading its own homework.
How do I stop an agent loop from running forever?
Pin the stopping condition before you start: measurable passes (tests green, an exit code, a score threshold) plus a hard cap like "or stop after 5 rounds, then summarize what is left." Every kit this tool generates includes both, plus tripwires that force an immediate stop when the loop is clearly stuck.
What budget cap should I set?
Start tight - the kits here default to $3-$10 hard caps per run depending on risk, with a monthly ceiling for recurring loops - and raise only with run data. Teams have had to impose hard monthly per-engineer caps after agent spend ran away; the cap you set on day one is the cheap version of that lesson.
Does this tool call an LLM?
No. The kits are assembled deterministically in your browser from curated, task-specific templates. Same inputs, same kit, every time - and nothing you select leaves the page.
Which agent tools does the loop prompt work with?
Any harness that runs an agent in a loop: Claude Code (it pairs well with the /goal command, which evaluates a completion condition after every turn), Cursor, or your own script. Fill in the project-specific details - paths, thresholds, exact scope - before you run it.
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