skills.rest
ruvnet
ruvnetCOMMUNITY
Explore all skills by this author →
Website𝕏@ruvGitHub

gaia-architecture-comparison

Compares ruflo's GAIA benchmark harness against the Princeton HAL reference implementation.

70.1k|8.4k|Updated Jun 2, 2025
Search Tags:#gap analysis#pass-rate#ROADMAP#agent harness#HAL#architecture comparison#gaia benchmark
One-click install
npx skills add https://github.com/ruvnet/claude-flow --skill gaia-architecture-comparison
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gaia-architecture-comparison
Source: https://github.com/ruvnet/claude-flow/tree/main/plugins/ruflo-workflows/skills/gaia-architecture-comparison
Command: npx skills add https://github.com/ruvnet/claude-flow --skill gaia-architecture-comparison

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Teams iterating on GAIA benchmark agents lack a clear view of how their harness compares to reference implementations, making it hard to prioritize which architectural change yields the highest pass-rate improvement.

Core Features & Use Cases

  • Side-by-side architecture comparison: Maps ruflo's harness components (gaia-loader, gaia-agent, gaia-tools, voting, hardness routing, judge) against the Princeton HAL reference across dimensions like question count, web search, code execution, and file handling.
  • Gap analysis with impact ranking: Identifies primary gaps (real python_exec sandbox, full 165-question L1 set, Playwright-based browsing) and secondary gaps (file parsing, turn budget, system prompt tuning).
  • Prioritized improvement roadmap: Provides a P0-P3 table with expected pass-rate lift and effort estimates for each change.
  • Use Case: Before planning the next GAIA iteration, run this comparison to confirm that implementing a real code execution sandbox (E2B) is the highest-ROI change, then store findings in AgentDB memory for future runs.

Quick Start

Ask the agent to compare the ruflo GAIA harness against the HAL reference implementation and list the highest-impact capability gaps with an improvement roadmap.

Frequently Asked Questions about gaia-architecture-comparison

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

FAQPage Schema
How do I compare my GAIA benchmark harness against the HAL reference?▼

Run the comparison to map your harness components against HAL across dimensions like question count, web search, code execution, and file handling. The output includes a gap table and a prioritized improvement roadmap with expected pass-rate lift per change.

What is the biggest gap between ruflo and the HAL GAIA implementation?▼

The largest gap is the lack of a real code execution sandbox, since ruflo's python_exec tool is a stub while HAL uses a real Jupyter kernel. Implementing a sandbox via E2B, Pyodide, or subprocess is estimated to lift pass-rate by 15-25 percentage points.

Why is ruflo's GAIA L1 pass-rate lower than HAL's?▼

ruflo scores about 20.8% versus HAL's 74.6%, a roughly 54-point gap. Contributing factors include running only 53 of 300 L1 questions, a stubbed code execution tool, raw HTML fetching instead of a real browser, and limited file parsing.

Does ruflo have any advantages over the HAL reference harness?▼

Yes, ruflo adds self-consistency voting (Track A), hardness-based routing of questions to appropriate models and turn budgets (Track Q), and AgentDB memory for recalling successful strategies across runs. None of these exist in the HAL reference.

How many questions should I run for a comparable GAIA L1 score?▼

Run with --limit 165 to cover the full L1 question set. The default 53-question subset skews easier and underestimates the true pass-rate, making comparison with HAL's 300-question evaluation misleading.

Related Skills

Explore More Software Engineering Skills→
mvillmowmvillmow
18

benchmark-functions

Benchmark Python functions with warm-up iterations and statistical analysis.

Community
Intermediate
ammonfifeammonfife

bigmac-e2b

Create and manage BIGMAC E2B sandboxes for code execution and browser automation.

Community
Advanced
MystenLabsMystenLabs
83

memwal

Store encrypted AI agent memories on Walrus with on-chain ownership.

Official
Advanced
SPRAGESPRAGE

ruflo-builder

Scaffold ruflo agents, workflows, and swarms from project knowledge store data.

Community
Advanced