Aris Meta Optimize

Aris Meta Optimize is an AI Engineering skill for Claude Code, published by OpenLAIR in dr-claw.

1K stars116 forkson OpenLAIR/dr-clawAdded 2026/08/21Repository updated 2026/08/09

ai-agentsai-scientistauto-researchclaude-codeclaude-science-desktop-alternativeclaude-science-freeliterature-reviewpaper-writingresearch-assistant

Install in seconds

Install Aris Meta Optimize

Copy Aris Meta Optimize into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-meta-optimize ~/.claude/skills/aris-meta-optimize

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/OpenLAIR/dr-claw.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/aris-meta-optimize/SKILL.md in OpenLAIR/dr-claw
Installs to: ~/.claude/skills/aris-meta-optimize
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What Aris Meta Optimize does

Aris Meta Optimize analyzes ARIS usage logs and suggests changes to SKILL.md prompts, defaults, and workflow rules. Use it when optimizing the harness based on accumulated runs and manual overrides.

Aris Meta Optimize is cataloged under AI Engineering on DirSkills. Aris Meta Optimize comes from a repository tagged ai-agents, ai-scientist, auto-research, claude-code and claude-science-desktop-alternative.

Documentation

README

Excerpt

Meta-Optimize: Outer-Loop Harness Optimization for ARIS

Analyze accumulated usage logs and propose optimizations for: $ARGUMENTS

Context

ARIS is a research harness — a system of skills, bridges, workflows, and artifact contracts that wraps around LLMs to orchestrate research. This skill implements a prototype outer loop that observes how the harness is used and proposes improvements to the harness itself (not to the research artifacts it produces).

Inspired by Meta-Harness (Lee et al., 2026): the key insight is that harness design matters as much as model weights, and harness engineering can be partially automated by logging execution traces and using them to guide improvements.

What This Skill Optimizes (Harness Components)

This is the opening of the README. Read the full README on GitHub.

Commands Aris Meta Optimize provides

Slash commands named in this skill’s SKILL.md, listed in the order they first appear.

/aris-meta-optimize

Frequently asked about Aris Meta Optimize

What else does OpenLAIR publish alongside Aris Meta Optimize?
Aris Meta Optimize is one of 25 skills that DirSkills catalogs from OpenLAIR/dr-claw, the repository it ships in. Its siblings there include ARIS Infra, Ablation Planner and Academic Researcher. Each one is a separate skill with its own page in this directory, installs the same way Aris Meta Optimize does, and is maintained by OpenLAIR in that same repository. The rest of the collection is listed on the OpenLAIR/dr-claw page.
How does Aris Meta Optimize compare to other AI Engineering skills?
Aris Meta Optimize ranks #1337 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Aris Meta Optimize against them. Open each page to compare what they document and how they install.