Overview
The material organization assistant is used to answer "what is the key point of this material", financial materials, risk disclosures, and evidence review. It is suitable for operations, marketing, technical, and product teams to call after clarifying business goals, content materials, or analysis targets. It will combine inputs such as investment research viewpoints and material excerpts, pasted research report viewpoints, meeting minutes summaries, news facts, financial indicators, or differences across multiple materials. It organizes the key context and outputs summaries, diagnostic conclusions, action recommendations, and reusable deliverables, making it easy to continue execution, review, or delivery.
When to use
Applicable scenarios
- The user asks questions such as "what is the key point of this material" and needs to quickly break down goals, determine priorities, and form executable results
- Operations, marketing, technical, and product teams need to generate summaries, diagnostic conclusions, action recommendations, and reusable deliverables around the material organization assistant
- The user has already prepared the target and research scenario (describe the target, industry, market, research purpose, time range, and usage scenario.), public material links (fill in publicly accessible announcements, exchange disclosures, company official websites, news, or data pages.), and investment research viewpoints and material excerpts (paste research report viewpoints, meeting minutes summaries, news facts, financial indicators, or differences across multiple materials.), and hopes to organize them into executable analysis or optimization results
- The user needs to turn materials related to the material organization assistant into clear conclusions, priorities, and next actions
How to call
Call the AI Skills API directly through the exported Python runner:
Command example
Basic call
python3 scripts/run.py --params '{}'
Call with common parameters
python3 scripts/run.py --params '{"assetContext":"标的与研究场景"}'
Parameter description
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
assetContext |
string | No | - | Describe the target, industry, market, research purpose, time range, and usage scenario |
marketDataLink |
string | No | - | Fill in publicly accessible announcements, exchange disclosures, company official websites, news, or data pages; a complete accessible URL must be provided |
researchNoteText |
string | No | - | Paste research report viewpoints, meeting minutes summaries, news facts, financial indicators, or differences across multiple materials |
researchPackFile |
string | No | - | Upload research reports, meeting minutes, financial statement excerpts, announcements, data tables, or comparison materials |
comparisonBasisNotes |
string | No | - | Supplement the dimensions to be compared, key assumptions, areas where conclusions cannot be drawn, and facts to be verified |
researchCompareFocus |
string | No | 观点差异 |
Select the direction that needs the highest priority in this investment research material comparison summary; optional values:观点差异、事实一致性、风险因素、待核实问题 |
See the complete machine-readable parameter structure at references/form-schema.json。
Parameter value reference
This skill currently has no categorical parameters that require additional lookup.
Supported input formats
This skill directly accepts JSON parameters; if the parameters contain a link field, please provide a complete, accessible URL.
Example request
The example parameters below can be passed directly to scripts/run.py, the runner will send them to the AI Skills API.
python3 scripts/run.py --params '{"assetContext":"标的与研究场景"}'
Equivalent --params JSON：
{
"assetContext": "标的与研究场景"
}
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: extract key context and basis for judgment by combining the target and research scenario (explain the target, industry, market, research purpose, time range, and use case.), publicly accessible links (provide publicly accessible announcements, exchange disclosures, company official websites, news, or data pages.), and investment research views and material excerpts (paste research report views, meeting summary excerpts, news facts, financial indicators, or differences among multiple materials.).
- Next steps: provide priorities, execution suggestions, or a content framework that can be further processed.
Suggestions for using the results
- First determine whether the output answers the user's core question about the "Material Organization 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 original materials before running.
Preparation before running
AISKILLS_BASE_URL: defaulthttps://ai-skills.aiAISKILLS_API_KEY: required, used for authenticated callsAISKILLS_TENANT_ID: defaultdefault