Overview
The business diagnostic assistant is used to answer "how should this be done," content operations, new media, and topic selection. It is suitable for operations, marketing, content media, and e-commerce to call after clarifying business goals, content materials, or analysis targets. It combines inputs such as comment and feedback sets, pasted comments, direct messages, customer service feedback, danmaku, or desensitized text from community discussions, 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 raise questions like "how should this be done" and need to quickly break down goals, determine priorities, and form executable results
- Operations, marketing, content media, and e-commerce need to generate summaries, diagnostic conclusions, action recommendations, and reusable deliverables around the business diagnostic assistant
- Users have already prepared comment and feedback sets (pasted comments, direct messages, customer service feedback, danmaku, or desensitized text from community discussions), uploaded comment exports (uploaded comment tables, customer service tickets, community records, NPS or tag statistics), comment source links (publicly accessible video, note, product page, post, or review page links), and want to organize them into executable analysis or optimization results
- Users need to turn business diagnostic assistant-related materials into clear conclusions, priorities, and next-step actions
How to Call
Call the AI Skills API directly through the exported Python runner:
Command Examples
Basic Call
python3 scripts/run.py --params '{}'
Call with Common Parameters
python3 scripts/run.py --params '{"commentCorpusText":"评论与反馈集合"}'
Parameter Description
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
commentCorpusText |
string | No | - | Pasted comments, direct messages, customer service feedback, danmaku, or desensitized text from community discussions |
commentExportFile |
string | No | - | Uploaded comment tables, customer service tickets, community records, NPS or tag statistics |
commentSourceLink |
string | No | - | Fill in publicly accessible video, note, product page, post, or review page links; a complete accessible URL is required |
brandServiceContext |
string | No | - | Explain the product/service, channel, campaign milestones, user groups, recent controversies, and operational goals |
responsePolicyNotes |
string | No | - | Supplement committable matters, content that cannot be responded to, customer service rules, escalation paths, and responsible teams |
sentimentActionFocus |
string | No | 情绪分类 |
Select the direction that this comment sentiment action card most needs to prioritize; optional values:情绪分类、根因归纳、回复建议、升级处理 |
For the complete machine-readable parameter structure, see 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; if a parameter contains a link field, pass a complete, accessible URL.
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 '{"commentCorpusText":"评论与反馈集合"}'
Equivalent --params JSON：
{
"commentCorpusText": "评论与反馈集合"
}
Example Results
{
"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 the comment and feedback collection (paste anonymized text from comments, direct messages, customer service feedback, bullet comments, or community discussions.), upload comment export (upload comment tables, customer service tickets, community records, NPS, or tag statistics.), comment source links (fill in publicly accessible links to videos, posts, product pages, threads, or review pages.) to extract key context and judgment basis.
- 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 given.
- If there is little input material, it is recommended to have the user supplement the goals, audience, constraints, or original materials before running.
Preparation Before Running
AISKILLS_BASE_URL: defaulthttps://ai-skills.aiAISKILLS_API_KEY: required, used for authenticated callsAISKILLS_TENANT_ID: defaultdefault