Awesome/awesome-copilot
1
0
Fork 0
mirror of https://github.com/github/awesome-copilot.git synced 2026-02-22 03:15:13 +00:00
Code Issues Packages Projects Releases Wiki Activity

fix: Correct spelling errors found by Codespell

Browse Source
This commit is contained in:
Jeremy Kohn
2026-02-02 00:00:31 -06:00
parent ccdfd66cc2
commit bb146c059f
7 changed files with 9 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
prompts/cosmosdb-datamodeling.prompt.md
View File

@@ -41,7 +41,7 @@ Purpose: Capture all details, evolving thoughts, and design considerations as th
- **Domain**: [e.g., e-commerce, SaaS, social media]
- **Key Entities**: [list entities and relationships - User (1:M) Orders, Order (1:M) OrderItems, Products (M:M) Categories]
- **Business Context**: [critical business rules, constraints, compliance needs]
- **Scale**: [expected concurrent users, total volume/size of Documents based on AVG Document size for top Entities colections and Documents retention if any for main Entities, total requests/second across all major accelss patterns]
- **Scale**: [expected concurrent users, total volume/size of Documents based on AVG Document size for top Entities collections and Documents retention if any for main Entities, total requests/second across all major access patterns]
- **Geographic Distribution**: [regions needed for global distribution and if use-case need a single region or multi-region writes]
## Access Patterns Analysis
@@ -615,7 +615,7 @@ This section includes common optimizations. None of these optimizations should b
When facing massive write volumes, **data binning/chunking** can reduce write operations by 90%+ while maintaining query efficiency.
**Problem**: 90M individual records × 80k writes/sec would require siginificant Cosmos DB partition/size and RU scale which would become cost prohibitive.
**Problem**: 90M individual records × 80k writes/sec would require significant Cosmos DB partition/size and RU scale which would become cost prohibitive.
**Solution**: Group records into chunks (e.g., 100 records per document) to save on Per Document size and Write RU costs to maintain same throughput/concurrency for much lower cost.
**Result**: 90M records → 900k documents (95.7% reduction)

2
prompts/update-avm-modules-in-bicep.prompt.md
View File

@@ -5,7 +5,7 @@ tools: ['search/codebase', 'think', 'changes', 'web/fetch', 'search/searchResult
---
# Update Azure Verified Modules in Bicep Files
Update Bicep file `${file}` to use latest Azure Verified Module (AVM) versions. Limit progress updates to non-breaking changes. Don't output information other than the final outout table and summary.
Update Bicep file `${file}` to use latest Azure Verified Module (AVM) versions. Limit progress updates to non-breaking changes. Don't output information other than the final output table and summary.
## Process