技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 367 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：可疑
Package：andyxinweiminicloud/clone-farm-detector
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：可疑
OpenClaw 评估
The skill's stated purpose (detecting clone-farming) is plausible, but the instructions are vague about how data is acquired/processed and the declared runtime needs (curl, python3) are not accompanied by any code or concrete API usage—this mismatch warrants caution before installing or running it.
目的
Name and description (detect clone farming in a marketplace) align with requiring network fetch and analysis tools. However, the skill declares required binaries (curl, python3) despite being instruction-only and providing no scripts; that's plausible but not strictly justified by the materials provided. No environment variables or credentials are requested, which is consistent with a read-only public-scan use case, but the skill does not expl…
说明范围
SKILL.md describes expected inputs (Capsule/Gene JSONs, publisher node id, or search term) and outputs, and lists what it checks, but it lacks concrete runtime instructions: it does not specify how to fetch marketplace data, what endpoints to call, or whether fetching requires credentials. The document also doesn't say whether any collected code or metadata will be transmitted externally. The lack of precise commands or safe-handling guidance …
安装机制
There is no install spec and no code files — lowest-risk install surface. No downloads or package installs are declared.
证书
The skill requests no environment variables or credentials, which is proportionate for a public-data analysis. That said, realistically scanning publisher catalogs or private marketplace APIs may require credentials or elevated access; the absence of any guidance about credential requirements or safe handling is a gap. If you plan to feed private marketplace data, be aware credentials might be needed and are not declared here.
持久
The skill does not request persistent/always-on presence (always: false) and does not request other skills' configs or system-wide settings. Autonomous invocation is allowed (the platform default) but not excessive here.
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Clone Farm Detector」。简介：Helps detect clone farming and reputation gaming in AI agent marketplaces. Iden…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/andyxinweiminicloud/clone-farm-detector/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: clone-farm-detector
description: >
Helps detect clone farming and reputation gaming in AI agent marketplaces.
Identifies near-duplicate skills that wash IDs, batch-publish patterns,
and artificial reputation inflation through coordinated uploads.
version: 1.0.0
metadata:
openclaw:
requires:
bins: [curl, python3]
env: []
emoji: "🧬"
---
# 40% of Marketplace Skills Are Clones — Detect Gene Farming Before It Erodes Trust
> Helps identify coordinated clone campaigns that flood agent marketplaces with near-duplicate skills to game reputation systems.
## Problem
Agent marketplaces rank skills by popularity, downloads, and publisher reputation. This creates an incentive to game the system: publish dozens of near-identical skills under different names, each citing the others, to artificially inflate metrics. The result? Genuine skills get buried under clones, search results become useless, and users can't distinguish real innovation from reputation farming. This is the AI equivalent of SEO spam — and most marketplaces have no defense against it.
## What This Checks
This detector examines a set of marketplace skills for clone farming indicators:
1. **Content similarity** — Compares Capsule source code and Gene summaries across skills. Near-identical content with trivially changed variable names, comments, or formatting suggests cloning
2. **Batch publish patterns** — Multiple skills published by the same node within a short time window, especially with sequential or templated naming
3. **ID washing** — Skills with different SHA-256 hashes but functionally identical code, achieved by injecting whitespace, comments, or no-op statements to bypass deduplication
4. **Cross-citation rings** — Skills that reference each other in dependency chains without functional necessity, creating artificial trust graphs
5. **Metadata templating** — Identical description structures, same emoji sets, copy-paste summaries with only the noun changed
## How to Use
**Input**: Provide one of:
- A list of Capsule/Gene JSON objects to compare
- A publisher node ID to scan their published catalog
- A marketplace search term to check top results for cloning
**Output**: A structured report containing:
- Cluster groups of similar/identical skills
- Similarity scores between flagged pairs
- Publishing timeline analysis
- Risk rating: CLEAN / SUSPECT / FARMING
- Evidence summary for each cluster
## Example
**Input**: Scan top 10 results for "code formatter" on marketplace
```
🧬 FARMING DETECTED — 2 clone clusters found
Cluster A (4 skills, 92% avg similarity):
- "python-formatter-pro" published 2024-12-01 08:01
- "py-code-beautifier" published 2024-12-01 08:03
- "format-python-fast" published 2024-12-01 08:07
- "python-style-fixer" published 2024-12-01 08:12
Publisher: same node (node_a8f3...)
Technique: variable rename + comment injection
ID washing: 4 unique hashes, 1 functional implementation
Cluster B (2 skills, 87% similarity):
- "js-lint-helper" published 2024-12-02
- "javascript-lint-tool" published 2024-12-02
Publisher: same node (node_a8f3...)
Cross-cites Cluster A skills as "dependencies"
Total: 6/10 top results are clones from one publisher.
Recommendation: Flag publisher for review. Genuine skills in results: 4/10.
```
## Limitations
Similarity detection helps surface likely clones but cannot prove intent. Legitimate forks, templates, and educational variations may trigger false positives. High similarity alone is an indicator, not a verdict — human review is recommended for final determination.