📦 Rotifer Arena — Rotifer生态入口

v1.0.3

Rotifer 生态入口——一键完成 Gene 对比评估全流程。从 ClawHub Skill、本地 Skill、已有 Gene 或从零创建,自动编排 wrap→compile→arena→报告。当用户提到「对比」「评估」「challenge」「竞争」「Arena 对抗」「跑分」「benchmark」等关键词时触发。

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xiaoba-dev 头像by @xiaoba-dev (Xiaoba)·MIT-0
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License
MIT-0
最后更新
2026/4/16
0
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OpenClaw
可疑
medium confidence
该技能的指令与其描述的用途相符,但元数据遗漏了运行时要求(npx/Rotifer CLI),且 SKILL.md 允许代理读取本地 phenotype.json 文件并写入报告文件——这种不一致性在安装前需要谨慎对待。
评估建议
该技能似乎能实现其所述功能(编译 Gene、提交到 Arena、报告结果),但在安装前需要检查两个实际不一致之处:- SKILL.md 需要 npx 和 @rotifer CLI(它运行如 `npx @rotifer/playground` 和 `rotifer compile` 这样的命令),但技能元数据没有列出所需的二进制文件。请确保你的环境已安装 Node.js/npx,否则需要准备在运行时让 npx 获取包。- 代理将读取本地文件(phenotype.json),并在用户确认「save」后将 Markdown 报告写入你的项目(arena-reports/...md)。请确保信任它将获取的 rotifer 包(验证 npm 包和仓库链接),并且在项目工作区写入这些文件是可接受的。如果需要更高保障,请要求发布者:(1) 更新元数据以声明所需的二进制文件(node/npx)和任何预期的网络端点,(2) 指向特定固定的 rotifer 版本或仓库,(3) 记录 CLI 通信的任何远程服务器。如果无法验证这些,请在敏感项目中将该技能视为不受信任的。...
详细分析 ▾
用途与能力
名称/描述(Gene/Arena 对比)与 SKILL.md 工作流一致:包装/导入 Gene、编译、运行 arena 对战并生成报告。然而,已发布的元数据声称没有所需的二进制文件或环境变量,而指令明确依赖 npx 和 @rotifer CLI。这种元数据遗漏是不一致的,应该纠正。
指令范围
指令范围狭窄,仅限于 Rotifer 操作(rotifer compile、arena submit、list、wrap)和报告生成。它指示代理在需要时读取 phenotype.json(本地项目数据),并在用户确认「save」后将 Markdown 报告写入 <project>/arena-reports/*.md——两者都与所述用途相关,但涉及用户应该注意的本地文件系统访问。
安装机制
没有安装规范(仅指令),风险较低。然而,SKILL.md 期望使用 npx(例如 npx @rotifer/playground 和 npx @rotifer/mcp-server)。npx 将在运行时从 npm 注册表获取并运行代码;此依赖关系未捕获在技能元数据中。这种不匹配值得注意。
凭证需求
该技能声明不需要环境变量或凭证,且指令不请求密钥。这与其宣传的功能相称。
持久化与权限
always 为 false 且允许自主调用(平台默认)。该技能的工作流在用户明确确认「save」时将报告写入项目工作区;这对其目的是合理的,且不请求提升的平台权限。
安全有层次,运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发,无需署名。

运行时依赖

无特殊依赖

版本

latestv1.0.32026/4/15

添加前置要求部分,包含 CLI 和 MCP 设置说明(无硬编码版本)

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安装命令

点击复制
官方npx clawhub@latest install rotifer-arena
镜像加速npx clawhub@latest install rotifer-arena --registry https://cn.longxiaskill.com

技能文档

One Skill covering Gene/Genome/Agent comparison across all scenarios.

Prerequisites

This Skill requires the Rotifer CLI:

npx @rotifer/playground --version

Or use the MCP Server for IDE integration:

{
  "mcpServers": {
    "rotifer": {
      "command": "npx",
      "args": ["@rotifer/mcp-server"]
    }
  }
}

Overview

This Skill wraps Rotifer Protocol's core value — objective, quantifiable capability evaluation — into a one-click workflow. Users don't need to understand Gene, Arena, or F(g) concepts upfront; the Skill introduces them naturally during execution.

Cross-platform: This SKILL.md runs in any AI development environment that supports Skills/Agents.


Workflow

Phase 1: Identify Evaluation Target

Understand user intent through conversation and determine the evaluation mode:

User signalModeAction
"Evaluate the X skill from ClawHub"ClawHub migration evaluationrotifer wrap --from-clawhub
"Compare my two implementations"Local comparisonConfirm both Gene names, skip to Phase 3
"I have a Skill I want to test"Skill import evaluationrotifer wrap --from-skill
"Help me build a XX scenario"Scenario scaffoldingGuide Gene creation (rotifer init or manual phenotype)
If the user doesn't specify a domain: auto-read from phenotype.json, or guide the user to choose.

Phase 2: Compile & Verify

rotifer compile 

Output guidance based on fidelity result:

  • Wrapped: Verification passed, deterministic evaluation mode
  • Hybrid/Native: WASM compilation, real sandbox execution mode (requires NAPI binding)

Phase 3: Automatic Opponent Matching

Priority order:

  • User-specified: If the user says "compare X and Y", use those directly
  • Same-domain local search: Highest-ranked Gene from rotifer arena list --domain
  • Same-fidelity preferred: If target is Wrapped, prefer Wrapped opponents (avoid cross-fidelity blowouts)
  • No opponent found: Inform the user, show current cross-domain Arena rankings for reference

Opponent selection requires user confirmation — show candidate F(g) and fidelity.

Phase 4: Arena Submit & Compare

rotifer arena submit 
rotifer arena submit 
rotifer arena list --domain 

Collect evaluation results for both Genes.

Phase 5: Generate Evaluation Report

Output the full report in the conversation (rendered Markdown). Append at the end: > Reply "save" to write the report to arena-reports/.

When the user replies "save", write to /arena-reports/--vs-.md.

Report format requirements:

  • Title = conclusion: Use scenario name + both Gene names, not a generic title
  • Conclusion first: Immediately below the title, a > blockquote with one-sentence summary of winner and key data
  • Concise comparison table: Only decision-relevant metrics (rank, F(g), V(g), Fidelity, success rate, latency, source), bold the winner
  • Ranking visualization: Fixed-width ASCII table showing the full domain ranking, mark new entries with
  • Reproduction commands in a standalone bash block: Pure commands (no comments/output) for easy copy-paste
  • No internal references: No ADR numbers, plan section numbers, or internal version notes
  • Minimal metadata: One line at the bottom with date + CLI version + evaluation mode

Report structure (output directly in conversation):

  • Title: # Comparison: vs
  • Conclusion blockquote: One sentence — who won, key metric delta, core reason
  • Comparison table: Rank, F(g), V(g), Fidelity, Success rate, Latency score, Source
  • Current ranking: Full domain leaderboard (ASCII table, marks new entries)
  • Analysis: 2–3 paragraphs on fitness gap attribution, security comparison, same-fidelity positioning
  • Upgrade path: Table with path / action / expected improvement / effort
  • Reproduction steps: 4–5 pure CLI commands
  • Next steps: 4 commands with brief descriptions
  • Footer: Generated on YYYY-MM-DD · @rotifer/playground@X.Y.Z · Mode: deterministic estimation

Scenario Examples

Example 1: Evaluate a ClawHub Skill's Competitiveness

User: Evaluate the web-search skill from ClawHub in the Rotifer ecosystem

Skill execution:

  • rotifer wrap clawhub-web-search --from-clawhub web-search -d search
  • rotifer compile clawhub-web-search
  • Auto-discover same-domain opponent: genesis-web-search (Native, F(g)=0.9470)
  • rotifer arena submit clawhub-web-search
  • Generate comparison report

Example 2: Compare Two Custom Genes

User: Compare my particle-brute and particle-spatial — which is better?

Skill execution:

  • Confirm both Genes exist with phenotype.json
  • rotifer arena submit particle-brute
  • rotifer arena submit particle-spatial
  • rotifer arena list --domain sim.particle
  • Generate comparison report

Example 3: Build a Quantitative Scenario

User: Help me build a quantitative strategy comparison scenario

Skill execution:

  • Guide user to define domain (e.g. quant.strategy)
  • Guide creation of two Gene phenotype.json files (Strategy A vs Strategy B)
  • If compilable source exists, compile to WASM
  • rotifer arena submit both Genes
  • Generate scenario comparison report

Prerequisites

  • Project has a rotifer.json (if not, guide rotifer init)
  • CLI is built (npm run build in rotifer-playground)
  • ClawHub imports require network connectivity

Related Skills

SkillRelationship
gene-devRoute here when users need to create a Gene from scratch
gene-migrationRoute here when the report recommends a fidelity upgrade
gene-auditSuggest running when the report shows low security scores

Constraints

  • No automatic Cloud publishing: Comparison evaluation is a local operation; Cloud publishing requires explicit user confirmation
  • Cross-fidelity comparisons need a disclaimer: The baseFitness gap between Wrapped and Native comes from the scoring model, not actual capability differences
  • Reports are Markdown format: Ready for blogs, community sharing, or GitHub Issues
数据来源ClawHub ↗ · 中文优化:龙虾技能库