Research Proposal Loop is an AI Engineering skill for Claude Code, published by gaasher in Agent-Loop-Skills.
Research Proposal Loop iteratively grades and revises an existing research proposal using literature-grounded feedback. Use it when a proposal needs stronger soundness, contribution, and evidence before it passes a target score.
Research Proposal Loop is cataloged under AI Engineering on DirSkills. Research Proposal Loop comes from a repository tagged agent-skills, agentic-loops, agentic-workflows, ai-agents and anthropic.
Documentation
The artifact is a research proposal; the feedback signal is ScholarEval (literature-grounded
Soundness + Contribution) turned into a 0-100 grade by a Judge against the fixed rubric.md.
Each iteration evaluates → grades → revises until the grade clears <pass_threshold> or the
budget runs out.
This is the opening of the README. Read the full README on GitHub.
Research Proposal Loop is one of 25 skills that DirSkills catalogs from gaasher/Agent-Loop-Skills, the repository it ships in. Its siblings there include Alpha Evolve, Anomaly Investigation and Blue Team. Each one is a separate skill with its own page in this directory, installs the same way Research Proposal Loop does, and is maintained by gaasher in that same repository. The rest of the collection is listed on the gaasher/Agent-Loop-Skills page.
Research Proposal Loop ranks #3347 by stars among the 3670 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 Research Proposal Loop against them. Open each page to compare what they document and how they install.
Research Proposal Loop is one of 25 skills cataloged on DirSkills from gaasher/Agent-Loop-Skills.
Research Proposal Loop is one of 3670 AI Engineering skills cataloged on DirSkills, ranked #3347 by stars among them.