Overview
The business diagnostic assistant is used to answer "how should this be done," e-commerce operations, product conversion, and user feedback. It is suitable for operations, marketing, sales, and product teams to invoke after clarifying business goals, content materials, or analysis targets. It combines negative reviews and feedback, pasted negative reviews, follow-up reviews, buyer feedback, customer service records, return reasons, or after-sales notes. and other inputs, organizes key context, and outputs summaries, diagnostic conclusions, action recommendations, and reusable deliverables for continued execution, review, or delivery.
When to Use
Applicable Scenarios
- Users ask questions such as "how should this be done," and need to quickly break down goals, determine priorities, and form executable results
- Operations, marketing, sales, and product teams need to generate summaries, diagnostic conclusions, action recommendations, and reusable deliverables around the business diagnostic assistant
- Users have already prepared uploaded review data (supports review exports, customer service records, after-sales spreadsheets, or review documents.), negative reviews and feedback (pasted negative reviews, follow-up reviews, buyer feedback, customer service records, return reasons, or after-sales notes.), product and page information (supplement category, price, specifications, selling points, page promises, target audience, and after-sales policy.), and want to organize them into executable analysis or optimization results
- Users need to turn materials related to the business diagnostic assistant into clear conclusions, priorities, and next actions
How to Invoke
Call the AI Skills API directly through the exported Python runner:
Command Examples
Basic Invocation
python3 scripts/run.py --params '{}'
Invocation with Common Parameters
python3 scripts/run.py --params '{"reviewFile":"上传评论数据"}'
Parameter Description
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
reviewFile |
string | No | - | Supports review exports, customer service records, after-sales spreadsheets, or review documents |
reviewText |
string | No | - | Pasted negative reviews, follow-up reviews, buyer feedback, customer service records, return reasons, or after-sales notes |
productInfo |
string | No | - | Supplement category, price, specifications, selling points, page promises, target audience, and after-sales policy |
analysisGoal |
string | No | 定位根因并给改进清单 |
Analysis goal; optional values:定位根因并给改进清单、降低差评率、降低退货率、优化客服话术、验证是否异常批次 |
orderContext |
string | No | - | Supplement platform, campaign, time range, batch, logistics, packaging, average order value, or return rate |
severityFocus |
string | No | 影响评分和复购的问题 |
Focus areas; optional values:影响评分和复购的问题、高频产品问题、强情绪投诉、物流包装问题、客服售后问题、页面预期不一致 |
customerSegment |
string | No | - | Describe user region, purchase scenario, new or returning customers, price sensitivity, or typical usage patterns |
See the complete machine-readable parameter structure at references/form-schema.json。
Parameter Value Reference
This skill currently has no categorical parameters that require an additional lookup table.
Supported Input Formats
This skill directly accepts JSON parameters and does not involve share link parsing.
Example Request
The example parameters below can be passed directly to scripts/run.py, and the runner will send them to the AI Skills API.
python3 scripts/run.py --params '{"reviewFile":"上传评论数据"}'
Equivalent --params JSON：
{
"reviewFile": "上传评论数据"
}
Example Return Result
{
"success": true,
"data": {
"message": "示例结果请以技能真实返回结构为准。"
},
"meta": {
"executionTime": 842,
"cached": false
}
}
Deliverables
- Summary, diagnostic conclusions, action recommendations, and reusable deliverables: organize the core results around the user's goals that can be directly read, reviewed, or delivered.
- Interpretation of input materials: combine uploaded review data (supports review exports, customer service records, after-sales spreadsheets, or review documents.), negative reviews and feedback (paste negative reviews, follow-up reviews, buyer feedback, customer service records, return reasons, or after-sales notes.), product and page information (supplement category, price, specifications, selling points, page promises, target audience, and after-sales policy.) to extract key context and bases for judgment.
- Next steps: provide priorities, execution recommendations, or a content framework that can be further developed.
Suggestions for Using the Results
- First determine whether the output answers the user's core questions about the "Business Diagnostic Assistant".
- Then check whether the results cover the summary, diagnostic conclusions, action recommendations, and reusable deliverables, and whether clear next steps are provided.
- If there is little input material, it is recommended to have the user supplement the goals, audience, constraints, or source materials before running.
Preparation Before Running
AISKILLS_BASE_URL: Defaulthttps://ai-skills.aiAISKILLS_API_KEY: Required, used for authenticated callsAISKILLS_TENANT_ID: Defaultdefault