arena

Spawns parallel candidate solutions to one task and synthesizes the strongest result.

136|8|Updated May 9, 2026
One-click install
npx skills add https://github.com/Sma1lboy/rove --skill arena-sma1lboy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: arena
Source: https://github.com/Sma1lboy/rove/tree/main/.agents/skills/pstack/skills/arena
Command: npx skills add https://github.com/Sma1lboy/rove --skill arena-sma1lboy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? A single attempt at a non-trivial artifact often locks in the wrong design shape early. This Skill runs multiple independent attempts at the same task, judges them against a rubric, and merges the best ideas into one verified result. ## Core Features & Use Cases - Parallel fan-out: Spawns N subagent candidates in one message, each writing to its own output path with a mandatory rationale. - Cross-judging and rubric scoring: Uses a separate judge model to score candidates criterion by criterion and recommend a base. - Grafting and synthesis: Ports the strongest ideas from losing candidates into the chosen base, recording grafts, rejections, and dropouts in a synthesis note. - Use Case: When designing a non-trivial module or document where one attempt risks the wrong structure, run the arena to compare several design directions and ship a synthesized, verified artifact. ## Quick Start Ask the agent to run the arena on your task, for example by saying "arena this: design the caching layer for the API service".

Frequently Asked Questions about arena

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

FAQPage Schema
How do I run multiple parallel attempts at the same coding task?▼

Use the arena workflow: frame a shared prompt with a rubric, spawn N subagents in one message with run_in_background set to true, and assign each its own output path. Each candidate produces the artifact plus a rationale for later comparison.

When should I use an arena approach instead of a single attempt?▼

Use it for non-trivial artifacts where one attempt would lock in the wrong design shape, such as architecture decisions or complex modules. Skip it for simple, well-understood tasks where parallel attempts add no signal.

How does the arena pick the best candidate?▼

A cross-judge subagent, preferably on a different model, scores each candidate against the rubric while the parent reads every candidate end to end. The base is picked on which candidate a maintainer can extend most easily, with agreement between judge and parent confirming the pick.

What happens if one arena candidate fails to produce output?▼

The workflow proceeds with N-1 candidates and records the dropout in the synthesis note. The remaining candidates are still judged, grafted, and verified normally.

What are the limitations of the parallel candidate approach?▼

If candidates wildly diverge, the task framing was under-specified and the arena should be reframed and re-run rather than averaged. The synthesized result also still requires verification, since the arena does not exempt output from normal scrutiny.