goals

Installation
SKILL.md

Process Goals in Prompt Optimization

Core Principle

Process goals (controllable intermediate actions) provide dense feedback signals; outcome goals (end-result demands) provide sparse, delayed feedback. This asymmetry explains why behavioral prompting dominates direct output demands.

Mechanism: Dense intermediate supervision → stable gradients → reliable optimization
Failure mode: Sparse outcome signal → high variance → reward hacking / hallucination

Goal Typology

Type Effect Size Prompt Analog Signal Density Failure Mode
Outcome d=0.09 "Give the correct answer" Sparse Hallucination, reward hacking
Performance d=0.44 "Achieve high accuracy" Proxy Goodhart's Law misalignment
Process d=1.36 "Think step-by-step" Dense Over-specification (rare)
Installs
6
GitHub Stars
5
First Seen
Jan 26, 2026
goals — zpankz/mcp-skillset