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Clawrank

Name: Clawrank
Author: joeycacciatore3

作者 JoeyCacciatore3 · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

总下载

当前安装

版本数

在 OpenClaw 中安装

/install nate-clawrank

功能描述

Agent performance scoring system for OpenClaw agents. 7 dimensions scored 0-10, crab-themed tiers, evidence-based, with trajectory tracking. Use at session e...

安全使用建议

This is an instruction-only scoring rubric and on its face is benign, but there are two things to check before enabling it broadly: (1) the SKILL.md says it "Integrates with agent-sync" but provides no endpoint, API, or credential instructions — ask the author how agent-sync integration works and whether it will send conversation content anywhere; (2) the rules require a one-line evidence entry per dimension, which means the agent will use session context (chat history, user prompts) to produce those lines — confirm you’re comfortable with that data being used/stored and whether peer review will transmit it externally. If you are unsure, test the skill in a restricted/sandboxed agent (or disable autonomous invocation) and verify where any peer-review data is posted and what auth it uses.

功能分析

Type: OpenClaw Skill Name: nate-clawrank Version: 1.0.0 The skill bundle is a purely instructional framework for an AI agent to self-evaluate its performance using a rubric called 'ClawRank'. It contains no executable code, network requests, or file system access, and the instructions in SKILL.md are limited to scoring logic and performance tiering without any malicious prompt injection or data exfiltration triggers.

能力评估

ℹ Purpose & Capability

The name, description, and instructions all align: this is a performance-scoring rubric for agents. However, the SKILL.md claims it "Integrates with agent-sync for peer review" but the skill declares no required env vars, endpoints, or instructions for how to access agent-sync. That integration claim is unexplained and may be a missing or incomplete dependency.

ℹ Instruction Scope

Instructions are tightly scoped to scoring seven dimensions, formatting the report, and tracking trajectory. They require the agent to produce short evidence lines per dimension which will naturally use session context (conversation history). The spec does not explicitly instruct reading unrelated system files or secrets, but it does hint at posting/recording to agent-sync without describing what data is sent or how — this ambiguity could lead to unexpected transmission of session content.

✓ Install Mechanism

Instruction-only skill with no install steps and no code files. That reduces surface area — nothing is downloaded or written to disk by the skill itself.

ℹ Credentials

The skill requests no environment variables or credentials, which is consistent with a local rubric. However, because it references agent-sync peer review, the lack of any declared credentials or endpoint is odd: if agent-sync requires auth, that requirement is not documented here.

✓ Persistence & Privilege

always is false (normal) and the skill does not request persistent configuration or system-wide changes. Autonomous invocation is allowed by default — expected for skills — but consider whether you want the agent to trigger self-evaluations without explicit user consent.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install nate-clawrank
安装完成后，直接呼叫该 Skill 的名称或使用 /nate-clawrank 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Initial release of ClawRank: a comprehensive agent performance scoring system for OpenClaw agents. - Introduces 7 evidence-based scoring dimensions (0–10 each), normalized to a 100-point scale. - Crab-themed performance tiers (Frozen to King Crab) with defined ranges and meanings. - Standardized session-ending format for score reports, including evidence for each dimension. - Weekly trajectory tracking for progress monitoring. - Peer review integration via agent-sync; enforces explanation on major self/peer disagreement. - Strict rules for scoring consistency, evidence, and trend focus.

元数据

Slug nate-clawrank

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题

Clawrank 是什么？

Agent performance scoring system for OpenClaw agents. 7 dimensions scored 0-10, crab-themed tiers, evidence-based, with trajectory tracking. Use at session e... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 99 次。

如何安装 Clawrank？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install nate-clawrank」即可一键安装，无需额外配置。

Clawrank 是免费的吗？

是的，Clawrank 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Clawrank 支持哪些平台？

Clawrank 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 Clawrank？

由 JoeyCacciatore3（@joeycacciatore3）开发并维护，当前版本 v1.0.0。