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lobster-rank

Name: lobster-rank
Author: bifang988

作者 bifang988 · GitHub ↗ · v3.0.2 · MIT-0

cross-platform ✓ 安全检测通过

161

总下载

当前安装

版本数

在 OpenClaw 中安装

/install lobster-rank

功能描述

Scan locally installed OpenClaw skills, collect evidence data, submit to the lobster ranking server for scoring, and let the user confirm uploading their res...

使用说明 (SKILL.md)

Lobster Rank

This skill scans your locally installed OpenClaw skills, collects metadata (skill names, structure flags, file counts, descriptions), and submits it to the lobster leaderboard server for scoring. No file contents, credentials, or personal data are sent — only structural metadata and heuristic signals. The scoring algorithm runs server-side.

Prerequisites

You need a Lobster API Key before submitting.

Get it at: https://lobster-rank.wondercv.com/me
Set it as an environment variable for convenience:
```
export OPENCLAW_API_KEY=your_key_here
```
Or pass it directly with --api-key on every command.

Privacy note: The script reads openclaw.json only to extract your apiKey field for authentication — no other fields are used or transmitted. It collects skill metadata (skill names, whether scripts/references/assets exist, file count, description) and heuristic signals (multi-model usage, log availability). No file contents, credentials, or personal data are sent. All data is submitted to the leaderboard server at https://lobster-rank.wondercv.com which is operated by the skill publisher.

Workflow

Step 1 — Scan & Submit

Run the scanner. It collects metadata about your installed skills and sends the raw data to the server for scoring.

python3 scripts/lobster_submit.py

With explicit API key:

python3 scripts/lobster_submit.py --api-key lbk_xxxxxxxxxxxx

Live Challenge mode (higher credibility, blends in a real-time challenge score):

python3 scripts/lobster_submit.py --mode live-challenge --challenge-score 85

Dry run (scan only, do not send to server):

python3 scripts/lobster_submit.py --dry-run

Step 2 — Review the Result

The script prints the score returned by the server. Present it to the user in a readable format, including:

Total score and grade
Title
Number of skills counted
Evaluation mode
Pending token expiry time

Ask the user: "要将这个成绩上传到排行榜吗？"

If they say yes, proceed to Step 3. If no, stop — the pending score stays valid for 24 hours and can be confirmed on the website.

Step 3 — Confirm Upload

Pass the pending_token from Step 2:

python3 scripts/lobster_submit.py --confirm \x3Cpending_token>

On success the script prints a confirmation. Tell the user their score is now on the leaderboard.

Step 4 — View on Leaderboard

Direct the user to:

https://lobster-rank.wondercv.com

Or their personal page:

https://lobster-rank.wondercv.com/me

Discovery Paths

The scanner checks these locations for skills:

~/.openclaw/workspace/skills
~/Library/Application Support/QClaw/openclaw/config/skills

And these for config / logs:

~/.openclaw/openclaw.json
~/Library/Application Support/QClaw/openclaw/config/openclaw.json
~/Library/Logs/QClaw/openclaw

To scan a custom path:

python3 scripts/lobster_submit.py --root /path/to/skills

Rules

Do not invent skills or fabricate evidence.
The scoring algorithm runs server-side; do not attempt to predict or influence it.
If no user-installed skills are found, stop and report the issue.
If the API key is missing or invalid, ask the user to retrieve it from https://lobster-rank.wondercv.com/me.
If the pending token has expired, re-run Step 1 to get a fresh evaluation.

安全使用建议

This skill will scan your OpenClaw skill folders and submit structural metadata and heuristic flags (skill names, file counts, a short description line, presence of scripts/assets, and keyword-based model routing signals) to https://lobster-rank.wondercv.com for scoring. That behavior is consistent with its description, but you should: (1) only provide an OPENCLAW_API_KEY you trust the Lobster operator to receive; (2) consider running with --dry-run first to inspect what the scanner finds locally before sending anything; (3) review the script if you are worried about sensitive data — it does not upload log or config contents, only a boolean/log-availability flag and extracted metadata, but it does read SKILL.md and openclaw.json to derive those signals; and (4) verify you trust the lobster-rank.wondercv.com operator before confirming uploads to the public leaderboard.

功能分析

Type: OpenClaw Skill Name: lobster-rank Version: 3.0.2 The lobster-rank skill is a leaderboard utility designed to scan a user's local OpenClaw environment and submit metadata to a ranking server (lobster-rank.wondercv.com). The script lobster_submit.py collects structural information about installed skills (file counts, directory presence, and descriptions from SKILL.md) and checks for the existence of logs and multi-model configurations. While it performs data collection and remote submission, its behavior is transparently documented, limited to the OpenClaw ecosystem (~/.openclaw), and requires explicit user confirmation and an API key, with no evidence of malicious intent or unauthorized access to sensitive system files.

能力评估

✓ Purpose & Capability

Name/description match what the files do: the included Python script scans skill directories, extracts metadata/flags, and submits them to a Lobster leaderboard server. The required OPENCLAW_API_KEY is appropriate for authenticating submissions.

ℹ Instruction Scope

The SKILL.md promises 'no file contents' are sent; the script does not upload full file contents but it does read SKILL.md files to extract a one-line description and to run heuristics (keyword scanning) that produce flags sent to the server. It also reads openclaw.json to extract an apiKey. This is within the advertised behavior but means the skill inspects local SKILL.md text and config files (not full contents) for heuristic signals.

✓ Install Mechanism

Instruction-only with an included Python script; no installers, external downloads, or exotic package installs are present. Risk from install mechanism is low.

✓ Credentials

Only an API key for the Lobster service (OPENCLAW_API_KEY) is required and the script also optionally reads the local openclaw.json to obtain that key. No unrelated credentials, secrets, or high‑privilege environment variables are requested.

✓ Persistence & Privilege

The skill does not request always:true, does not modify other skills or system settings, and is user‑invocable only. It does not persist extra privileges or write installers.

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 lobster-rank
安装完成后，直接呼叫该 Skill 的名称或使用 /lobster-rank 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

v3.0.2

Version 3.0.2 of lobster-rank - No file changes detected; documentation and functionality remain unchanged. - All features and workflow, including API key usage, privacy policy, and leaderboard integration, are consistent with the previous version. - Env var：OPENCLAW_API_KEY（required） - Local file：~/.openclaw/openclaw.json（read apiKey only） - Network：lobster-rank.wondercv.com

v3.0.0

网址入口修改

v2.0.1

No changes detected in this release. - No file changes were found between the previous and current version. - Documentation and functionality remain unchanged.

v2.0.0

lobster-rank 2.0.0 - Added explicit documentation of required dependencies: environment variable, network host, and local file access. - Updated server URLs in instructions and examples to use http://47.94.254.45. - Clarified privacy guarantees—only skill structure metadata and authentication are accessed/transmitted; no personal data or file contents are sent. - Specified the fields read from `openclaw.json` (apiKey only). - Improved and expanded the description of what evidence and signals are collected for ranking.

v1.0.0

Initial release of lobster-rank skill. - Enables scanning of locally installed OpenClaw skills and submitting evidence for ranking. - Integrates with the lobster ranking server for secure, server-side scoring. - Supports API key usage via environment variable or command-line flag. - Offers live challenge mode, dry-run, and confirmation workflow for leaderboard uploads. - Guides users through reviewing, confirming, and publishing their score. - Includes safeguards for missing skills, invalid API keys, and token expiry.

元数据

Slug lobster-rank

版本 3.0.2

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 5

常见问题

lobster-rank 是什么？

Scan locally installed OpenClaw skills, collect evidence data, submit to the lobster ranking server for scoring, and let the user confirm uploading their res... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 161 次。

如何安装 lobster-rank？

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

lobster-rank 是免费的吗？

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

lobster-rank 支持哪些平台？

lobster-rank 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 lobster-rank？

由 bifang988（@bifang988）开发并维护，当前版本 v3.0.2。