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TabithaFanny
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meta-optimize

Analyze ARIS usage logs and propose optimizations for harness components.

Updated May 29, 2026
Search Tags:#optimization#skill optimization#usage analysis#aris#meta-harness
One-click install
npx skills add https://github.com/TabithaFanny/ThesisX --skill meta-optimize-tabithafanny
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: meta-optimize
Source: https://github.com/TabithaFanny/ThesisX/tree/main/skills_imported/aris/skills/meta-optimize
Command: npx skills add https://github.com/TabithaFanny/ThesisX --skill meta-optimize-tabithafanny

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, Read, Write, Edit, Grep, Glob, Agent, mcp__codex__codex, mcp__codex__codex-reply, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill analyzes ARIS usage logs and proposes optimizations for SKILL.md files, reviewer prompts, and workflow defaults to improve efficiency and performance.

Core Features & Use Cases

  • Usage Data Analysis: Reviews logs for frequency, failure, convergence, and human intervention patterns.
  • Optimization Proposals: Suggests changes to prompts, parameters, rules, and workflow ordering.
  • Patch Generation: Generates concrete diffs for review and implementation.
  • Cross-Model Review: Uses GPT-5.4 xhigh for adversarial review of patch proposals.
  • Structured Report: Outputs a report with proposed changes, analysis, and recommendations.

Quick Start

Run /meta-optimize to check for optimization opportunities in ARIS's harness components based on usage data.

Frequently Asked Questions about meta-optimize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize skill prompts using usage log analysis?▼

Skill prompt optimization using usage log analysis reviews event frequency, failure, convergence, and human intervention patterns to propose targeted improvements for harness components.

What is the best way to analyze ARIS harness usage data for workflow improvements?▼

Analyzing ARIS harness usage data for workflow improvements involves reviewing event logs, proposing parameter and rule changes, and generating concrete diffs for collaborative review.

Can I use GPT-5.4 xhigh for adversarial review of optimization patches?▼

Yes, GPT-5.4 xhigh supports adversarial cross-model review of patch proposals, validating changes to SKILL.md files, reviewer prompts, and workflow defaults before implementation.

How do I generate concrete diffs for ARIS workflow parameter changes?▼

Generating concrete diffs for ARIS workflow parameter changes requires analyzing usage logs for failure patterns and outputting a structured report with proposed changes and recommendations.

When do I need usage log analysis for harness component optimization?▼

Usage log analysis for harness component optimization is needed when workflow efficiency drops, requiring evaluation of convergence patterns and human intervention events to propose prompt updates.

Does meta-optimize work with Bash and Grep dependencies for event analysis?▼

Yes, meta-optimize works with Bash, Grep, Read, Write, and Edit dependencies to parse usage logs, analyze event patterns, generate patches, and modify ARIS harness components.

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