ULW Loop is an AI Engineering skill for Claude Code, published by code-yeongyu in oh-my-openagent.
ULW Loop decomposes work into systematic, evidence-bound steps for durable, checkpointed goal execution, using subagents and manual QA channels. Use it for long-running, evidence-led delivery with git-tracked edits.
ULW Loop is cataloged under AI Engineering on DirSkills. ULW Loop comes from a repository tagged ai, ai-agents, anthropic, chatgpt and claude.
Documentation
Use this skill when the user asks for ulw-loop, ulw, durable goal execution, evidence-led work, manual QA, or checkpointed long-running delivery.
This skill is intentionally compact. The full workflow lives in references/full-workflow.md. Read only the sections needed for the current phase, then execute them exactly.
This is the opening of the README. Read the full README on GitHub.
ULW Loop is one of 21 skills that DirSkills catalogs from code-yeongyu/oh-my-openagent, the repository it ships in. Its siblings there include Codex QA, Dead Code Removal and Get Unpublished Changes. Each one is a separate skill with its own page in this directory, installs the same way ULW Loop does, and is maintained by code-yeongyu in that same repository. The rest of the collection is listed on the code-yeongyu/oh-my-openagent page.
ULW Loop ranks #77 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of ULW Loop against them. Open each page to compare what they document and how they install.
ULW Loop is one of 21 skills cataloged on DirSkills from code-yeongyu/oh-my-openagent.
ULW Loop is one of 2451 AI Engineering skills cataloged on DirSkills, ranked #77 by stars among them.