LLM Tails open-source bundle brings disciplined rules to coding agents
The author of LLM Tails says the MIT-licensed project combines Ponytail and LLM Wiki through prompts, hooks, and skills that encourage coding agents to read first, write minimally, and verify claims. The author says it has no dependencies and works with Claude Code, Cursor, GitHub Copilot, Codex, Gemini, Windsurf, Cline, and Kiro. Claims about smaller codebases, lower token use, and fewer hallucinations are not supported by numerical results, while the referenced same-prompt comparison image is not available in the supplied report.
LLM Tails packages read-first, minimal-output, and verification instructions into a zero-dependency bundle that its author says is compatible with several named coding agents.
| https://github.com/savadks95/LLM\_Tails I just published a GitHub repo a few days ago. It's a mix of Ponytail and LLM Wiki. It helps developers reduce codebase size with minimal code. It reduces overall token usage and AI hallucinations, and a couple of other fantastic things. The image is the test result of developing a small game with and without LLM Tails. Both used the exact same prompt LLM_Tails is an open-source prompt + hooks + skills bundle that makes the agent read before it writes, write the minimum, verify before it claims, and match your codebase. MIT, zero dependencies, works with Claude Code, Cursor, Copilot, Codex, Gemini, Windsurf, Cline, Kiro, and any agent that reads submitted by /u/savadks1818 [link] [comments] |
#LLM Tails#Ponytail#LLM Wiki#Claude Code#Cursor#GitHub Copilot#Codex#Gemini#Windsurf#Cline#Kiro