Source note
Loop Library for Engineers
Summary
The Loop Library is a collection of practical AI-agent workflows for software engineering and related product tasks. Each loop combines an objective with checks, evidence requirements, stopping conditions, and review or approval boundaries.
Problem
- General-purpose coding agents can make partial, unverifiable, or overly broad changes, making completion difficult to assess.
- Repeated engineering work such as documentation updates, refactoring, testing, debugging, benchmarking, and release preparation needs reliable procedures and explicit safeguards.
- The library matters because it turns loosely specified agent requests into bounded workflows that can produce reviewable artifacts and evidence.
Approach
- Provide reusable natural-language loops that define the task, sequence of actions, validation checks, failure handling, and terminal conditions.
- Require concrete evidence such as tests, benchmarks, screenshots, pull requests, logs, reviewer verdicts, or before-and-after comparisons.
- Use mechanisms including isolated worktrees, independent reviewers, holdout cases, regression tests, repeated runs, rollback checkpoints, and approval gates.
- Support installation and guided use through the Loopy agent skill, including commands such as
npx skills add Forward-Future/loopy --skill loopy -g.
Results
- The page reports 85 loops in the library.
- Examples cover documentation synchronization, architecture refactoring, production error repair, test coverage, SEO and AI-answer visibility, flaky-test remediation, dependency vulnerabilities, accessibility, backups, and agent collaboration.
- Individual loops specify measurable or auditable completion criteria, such as page loads under 50 ms, test coverage reaching 100%, 18 matches and 180 rounds for the repeated-game experiment, or a clean fresh-clone onboarding pass.
- The provided text reports no aggregate benchmark, success rate, user study, or comparison against baseline prompting; the strongest evidence is the breadth and specificity of the published workflow examples.