llm-tuning-patterns
✓LLM Tuning Patterns
Installation
SKILL.md
Evidence-based patterns for configuring LLM parameters, based on APOLLO and Godel-Prover research.
Different tasks require different LLM configurations. Use these evidence-based settings.
| maxtokens | 4096 | Proofs need space for chain-of-thought | | temperature | 0.6 | Higher creativity for tactic exploration | | topp | 0.95 | Allow diverse proof paths |
LLM Tuning Patterns Source: parcadei/continuous-claude-v3.
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill llm-tuning-patterns- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-01
- Updated
- 2026-02-18
Quick answers
What is llm-tuning-patterns?
LLM Tuning Patterns Source: parcadei/continuous-claude-v3.
How do I install llm-tuning-patterns?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/parcadei/continuous-claude-v3 --skill llm-tuning-patterns Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/parcadei/continuous-claude-v3
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-01