ms-customer-stories
npx skills add https://github.com/hihigash/ms-customer-stories-skill --skill ms-customer-stories
Agent 安装分布
Skill 文档
Microsoft Customer Stories
Overview
Search and retrieve customer stories from Microsoft’s official Customer Stories site via its internal API.
Workflow
- Analyze the user’s request to determine appropriate filters
- Run
scripts/search_stories.pywith selected filters to find matching stories - Review results and optionally run
scripts/fetch_story.pyon specific stories for full details - Summarize findings for the user
Prerequisites
Install requests in the Python environment: pip install requests
Step 1: Map User Request to Filters
Translate the user’s natural language request into API filter parameters. Consult references/filters.md for the complete list of available filter values.
Mapping guidelines:
| User mentions | Filter to use |
|---|---|
| Country/region names (Japan, US, etc.) | --region (e.g., asia/japan) |
| Product names (Azure, Teams, etc.) | --products (e.g., azure/azure-openai) |
| Industry terms (healthcare, finance, etc.) | --industry (e.g., healthcare) |
| Business concepts (AI, automation, etc.) | --business-need (e.g., artificial-intelligence) |
| Company size (SMB, enterprise, etc.) | --org-size (e.g., 50-999-employees) |
| Specific technology terms (RAG, etc.) | --query (free text search) |
Common mappings:
- “ä¸å°ä¼æ¥” / “SMB” â
--org-size 50-999-employeesor--org-size 1-49-employees - “大伿¥” / “Enterprise” â
--org-size 10000-employees - “RAG” / “æ¤ç´¢æ¡å¼µçæ” â
--query RAG+--products azure/azure-openai - “æ¥æ¬” â
--region asia/japan
Step 2: Search Stories
Run the search script:
python scripts/search_stories.py --products azure/azure-openai --region asia/japan --query "RAG" --top 10
Arguments:
--query/-q: Free text search--products/-p: Product filter (e.g.,azure/azure-openai,azure/azure-ai-search)--region/-r: Region filter (e.g.,asia/japan,europe/germany)--industry/-i: Industry filter (e.g.,healthcare,manufacturing)--business-need/-b: Business need (e.g.,artificial-intelligence)--org-size/-o: Organization size (e.g.,50-999-employees)--service/-s: Service filter (e.g.,fasttrack)--includes: Stories that include (e.g.,videos,partners)--top/-t: Number of results (default: 12)--skip: Pagination offset
Output is JSON with totalCount, hasMorePages, and stories array.
Step 3: Fetch Story Details
For interesting stories, fetch the full content:
python scripts/fetch_story.py 25666-softbank-corp-azure-ai-foundry
Accepts a story slug or full URL. Returns JSON with title, description, content.
Output Format
Always respond in the same language the user used. If the user asks in Japanese, reply in Japanese. If in English, reply in English.
Present results to the user in this format:
## Search Results: {totalCount} stories
### 1. {title}
- **Industry**: {industry}
- **URL**: {url}
- **Summary**: {summary from content}
### 2. {title}
...
When the user asks for details on a specific story, provide a more detailed summary of the story content including key challenges, solutions, and outcomes.