OpenAgentSkill Registry Manifest
Skill: dueling-autoresearch
Slug: gaasher-dueling-autoresearch
Category: research
Description: Use when the user wants two approaches raced head-to-head on a single shared metric — e.g. a classical/algorithmic lane vs an ML/learned lane, or any two strategies for the same task. Each lane runs its own analysis-first research loop confined to its lane, the lanes share a scoreboard and may borrow ideas across the boundary without abandoning their identity, and a shared eval keeps the head-to-head honest; loops until interrupted, reporting the current leader. Not for improving a single approach in isolation (use a single-track research loop), and not for picking between two finished artifacts in one shot (that is a one-time comparison).

Agent fit:
- Decision: 62/100 Prototype first
- Primary fit: Research agents
- Role: Fallback candidate

Supply profile:
- Track: Research and knowledge work
- Scenario: Research agents
- Applicable agents: Claude Code, CLI, Codex, Cursor
- Maintenance: 2mo since push
- Risk: Needs review

Trust:
- Trust score: 78/100 Strong shortlist
- Audit: 78/100 Needs review

Attribution:
- Status: Registry indexed
- Source: github fast track
- Creator: gaasher
- Claim URL: https://www.openagentskill.com/skills/gaasher-dueling-autoresearch#claim-this-skill

Install:
npx skills add gaasher/Agent-Loop-Skills --skill dueling-autoresearch

URLs:
- Web: https://www.openagentskill.com/skills/gaasher-dueling-autoresearch
- API: https://www.openagentskill.com/api/agent/skills/gaasher-dueling-autoresearch
- Install API: https://www.openagentskill.com/api/skills/gaasher-dueling-autoresearch/install
- Repository: https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/dueling-autoresearch