Agent loops for coding agents
An agent loop is a prompt that keeps a coding agent working through one check-and-fix cycle until a condition you can measure is true: the build is green, coverage clears a target, an audit comes back clean. Each loop below is ready to paste into Claude Code, Cursor, or any agent with tools, with an iteration cap, stop rules, and the MCP servers that help it run.
Check queries, migrations, and pipelines against the data before anyone relies on them.
- Data
Query Until Verified
Write a SQL query for a business question, run it on a read-only connection, and refine it until row counts, totals, and sanity checks reconcile.
Up to 6 iterationsOpen loop - Data
Data Checks Until Clean
Run data quality tests on a pipeline or model, trace each failure to the transformation that caused it, fix it, and rebuild until every test passes.
Up to 8 iterationsOpen loop - Data
Migration Round Trip
Apply a database migration to a scratch database, roll it back, apply it again, and compare schemas until the migration is clean in both directions.
Up to 6 iterationsOpen loop
What makes a good agent loop
- A settings block. Commands, targets, and limits sit at the top of the prompt, so you adapt a loop to your project by editing a few lines instead of rewriting it.
- One small change per pass. The agent runs a check, fixes one cause, and checks again. Small steps keep each change reviewable and stop one bad edit from snowballing.
- A stop condition the agent can verify. Exit codes, coverage numbers, and audit counts are things the agent can read from command output, so it knows when it is done instead of guessing.
- Hard limits and safety rules. Every loop has an iteration cap, a rule for when it is stuck, and a list of things it must never do, such as force-pushing, silencing tests, or touching production.
- The right tools. Loops run best when the agent can reach your repository, CI, browser, or database directly. Each loop page lists matching MCP servers from the directory, ranked by trust score.