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Ecommerce Return Intelligence
by
vx：17605205782
· GitHub ↗
· v1.0.0
· MIT-0
166
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Install in OpenClaw
/install ecommerce-return-intelligence
Description
分析退货原因并区分产品问题、预期错配、物流问题和描述问题。；use for ecommerce, returns, analysis workflows；do not use for 伪造订单数据, 替代客服系统.
README (SKILL.md)
电商退货洞察器
你是什么
你是“电商退货洞察器”这个独立 Skill，负责：分析退货原因并区分产品问题、预期错配、物流问题和描述问题。
Routing
适合使用的情况
- 分析这批退货原因
- 区分产品问题和预期错配
- 输入通常包含：退货记录 CSV、原因文本、商品信息
- 优先产出：退货概览、原因分类、后续动作
不适合使用的情况
- 不要伪造订单数据
- 不要替代客服系统
- 如果用户想直接执行外部系统写入、发送、删除、发布、变更配置，先明确边界，再只给审阅版内容或 dry-run 方案。
工作规则
- 先把用户提供的信息重组成任务书，再输出结构化结果。
- 缺信息时，优先显式列出“待确认项”，而不是直接编造。
- 默认先给“可审阅草案”，再给“可执行清单”。
- 遇到高风险、隐私、权限或合规问题，必须加上边界说明。
- 如运行环境允许 shell / exec，可使用：
python3 "{baseDir}/scripts/run.py" --input \x3C输入文件> --output \x3C输出文件>
- 如当前环境不能执行脚本，仍要基于
{baseDir}/resources/template.md与{baseDir}/resources/spec.json的结构直接产出文本。
标准输出结构
请尽量按以下结构组织结果：
- 退货概览
- 原因分类
- 高发问题
- 可优化项
- 需复核样本
- 后续动作
本地资源
- 规范文件：
{baseDir}/resources/spec.json - 输出模板：
{baseDir}/resources/template.md - 示例输入输出：
{baseDir}/examples/ - 冒烟测试：
{baseDir}/tests/smoke-test.md
安全边界
- 只做本地分析。
- 默认只读、可审计、可回滚。
- 不执行高风险命令，不隐藏依赖，不伪造事实或结果。
Usage Guidance
This skill appears internally consistent and safe for local use. Before running: 1) only run the script on directories/files you intend to analyze (avoid system or secrets directories); 2) if inputs contain PII or credentials, sanitize or omit them first; 3) run in an isolated environment if you want extra assurance (e.g., container or workspace copy); 4) review scripts/run.py if you want to confirm there are no network calls or unexpected writes (the script only reads files and can write the output file you specify). If you intend to automate actions (writes/notifications/changes) based on its output, treat the skill's output as a human-reviewed draft and implement explicit safeguards before performing external writes.
Capability Analysis
Type: OpenClaw Skill
Name: ecommerce-return-intelligence
Version: 1.0.0
The skill bundle is a legitimate tool designed for analyzing ecommerce return data and auditing file structures. The primary script, `scripts/run.py`, performs local file processing, CSV parsing, and includes a defensive pattern-matching feature to identify potential risks (like hardcoded secrets or dangerous shell commands) within input data. There is no evidence of data exfiltration, network communication, or malicious prompt injection; the code is well-structured and adheres to its stated purpose.
Capability Assessment
Purpose & Capability
Name/description (returns analysis) aligns with the included assets: resources/spec.json, template.md, examples, and scripts/run.py. The only declared binary is python3 which is necessary to run the helper script; there are no unrelated environment variables or credentials requested.
Instruction Scope
SKILL.md confines work to local analysis, explicitly advises read-only/auditable outputs, and instructs running the bundled python script or using the templates if execution is not allowed. The script reads files (including CSV/TSV/MD/py/js/sh), recursively lists files in directories, and performs pattern scanning — it does not execute discovered scripts or reach out to network endpoints. Because the script will read any file/directory the user supplies, users should avoid pointing it at system root or directories containing secrets/credentials.
Install Mechanism
There is no install spec and no network downloads; the skill is instruction+script-only and relies on the Python standard library. No archives or external package installs are performed.
Credentials
The skill requires no environment variables or external credentials. All operations are local and driven by user-provided input files; no secret-sounding env names or unrelated cloud credentials are requested.
Persistence & Privilege
always is false and the skill does not attempt to modify other skills or global agent configuration. The script can write an output file when given --output, which is expected behavior for a reporting tool.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install ecommerce-return-intelligence - After installation, invoke the skill by name or use
/ecommerce-return-intelligence - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of ecommerce-return-intelligence.
- Provides analysis of e-commerce return reasons, categorizing issues as product problem, expectation mismatch, logistics, or description issue.
- Outputs structured reports with overview, cause classification, frequent problems, suggested improvements, samples requiring review, and recommended actions.
- Operates in a read-only, auditable, and safe manner; explicitly avoids fabricating data or replacing customer service systems.
- Utilizes Python script if possible, otherwise generates results using provided templates and specifications.
- Clearly lists missing information for user confirmation and always provides reviewable drafts before executable recommendations.
Metadata
Frequently Asked Questions
What is Ecommerce Return Intelligence?
分析退货原因并区分产品问题、预期错配、物流问题和描述问题。；use for ecommerce, returns, analysis workflows；do not use for 伪造订单数据, 替代客服系统. It is an AI Agent Skill for Claude Code / OpenClaw, with 166 downloads so far.
How do I install Ecommerce Return Intelligence?
Run "/install ecommerce-return-intelligence" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Ecommerce Return Intelligence free?
Yes, Ecommerce Return Intelligence is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Ecommerce Return Intelligence support?
Ecommerce Return Intelligence is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux, win32).
Who created Ecommerce Return Intelligence?
It is built and maintained by vx：17605205782 (@52yuanchangxing); the current version is v1.0.0.
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