Set up and run an autonomous experiment loop for any optimization target. Gathers what to optimize, then starts the loop immediately. Use when asked to "run autoresearch", "optimize X in a loop", "set up autoresearch for X", or "start experiments".
- 📁 .github/
- 📁 assets/
- 📁 references/
- 📄 .gitignore
- 📄 LICENSE
- 📄 README.ja.md
A comprehensive AI marketing partner for DTC ecommerce. Combines multiple diagnostic and optimization skills powered by Attribuly first-party data.
- 📄 .DS_Store
- 📄 CLAUDE.md
- 📄 LICENSE
Generate high-converting App Store listing metadata (name, subtitle, keywords, and description) using proven ASO principles and keyword optimization.
Session bootstrap + workflows for Pathfinder semantic navigation tools. Covers: discovery protocol, tool chaining patterns (explore, impact, audit, debug), search optimization, LSP degraded mode, and error recovery.
- 📁 catalog/
- 📁 tests/
- 📄 .gitignore
- 📄 catalog_cli.py
- 📄 CHANGELOG.md
Catalog CLI audits Amazon Category Listing Reports (CLR files, .xlsx) for listing quality issues. It runs 12 query plugins covering missing attributes, title validation, bullet point optimization, product type checks, and more.
- 📁 assets/
- 📁 references/
- 📁 scripts/
- 📄 SKILL.md
Autonomous single-metric optimization loop driven by a program.md file. The agent edits one target file, runs an experiment, measures a metric, keeps improvements (git commit), reverts regressions (git reset), and loops indefinitely. Inspired by karpathy/autoresearch. Use for trading backtests, prompt optimization, site performance tuning, or any task with a clear numeric metric.
- 📁 test_cases/
- 📄 base.py
- 📄 dashboard.py
- 📄 SKILL.md
Self-improving optimization via Karpathy autoresearch pattern. Generates → evaluates → scores → mutates prompts/descriptions in a loop. Targets — tool-selection, system-prompt, skill, decision-parser. Use when "optimize tools", "autoresearch", "improve skill X", "self-improve prompts", "optimize tool descriptions".