ralph-wiggum
ralph-wiggum is an Execution & autonomous loops skill for AI agents, published by agrimsingh in the ralph-wiggum-cursor repository on GitHub. Skillspace rates ralph-wiggum B (87/100) and it passed the safety scan; the rating is based on static analysis only.
Implements the Ralph Wiggum autonomous iteration technique with deliberate context management. Use when building greenfield projects, iterating on well-defined tasks, or when continuous autonomous development is needed. Manages context like memory - tracks allocations, prevents redlining, and knows when to start fresh.
- Grade
- B
- Quality
- 87 / 100
- Safety
- Passed
- GitHub stars
- 494
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 1 collections
- Scope
- Portable: works in any project. General autonomous iteration and context-management technique
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.