Simplify telemetry to use GitHub.create_issue() only

- Remove complex PR/fork creation system
- Replace with simple GitHub.create_issue() for SciML/LinearSolve.jl
- Reduce token requirements to just "Issues: Write" permission
- Remove CSV dependency and unnecessary file generation functions
- Update documentation and user messaging for issue-based workflow
- Use only "benchmark-data" label for created issues
- Maintain local file fallback when GitHub creation fails

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

Author: ChrisRackauckas

lib/LinearSolveAutotune/Project.toml

@@ -7,7 +7,6 @@ version = "0.1.0"
 LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 Base64 = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
-CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 GitHub = "bc5e4493-9b4d-5f90-b8aa-2b2bcaad7a26"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
@@ -33,7 +32,6 @@ Metal = "dde4c033-4e86-420c-a63e-0dd931031962"
 LinearSolve = "3"
 BenchmarkTools = "1"
 Base64 = "1"
-CSV = "0.10"
 DataFrames = "1"
 GitHub = "5"
 Plots = "1"

lib/LinearSolveAutotune/src/LinearSolveAutotune.jl

@@ -2,7 +2,6 @@ module LinearSolveAutotune
 
 using LinearSolve
 using BenchmarkTools
-using CSV
 using DataFrames
 using PrettyTables
 using Preferences
@@ -76,15 +75,15 @@ include("preferences.jl")
 Run a comprehensive benchmark of all available LU factorization methods and optionally:
 
   - Create performance plots for each element type
-  - Upload results to GitHub telemetry  
+  - Create GitHub issue with telemetry data for community collection  
   - Set Preferences for optimal algorithm selection
   - Support both CPU and GPU algorithms based on hardware detection
   - Test algorithm compatibility with different element types
 
 # Arguments
 
   - `large_matrices::Bool = false`: Include larger matrix sizes for GPU benchmarking
-  - `telemetry::Bool = true`: Share results to GitHub issue for community data
+  - `telemetry::Bool = true`: Create GitHub issue with results for community data collection
   - `make_plot::Bool = true`: Generate performance plots for each element type
   - `set_preferences::Bool = true`: Update LinearSolve preferences with optimal algorithms
   - `samples::Int = 5`: Number of benchmark samples per algorithm/size
@@ -216,9 +215,9 @@ function autotune_setup(;
         end
     end
 
-    # Upload telemetry if requested
+    # Create GitHub issue with telemetry if requested
     if telemetry && nrow(successful_results) > 0
-        @info "📤 Preparing telemetry data for community sharing..."
+        @info "📤 Creating GitHub issue with benchmark data for community collection..."
         markdown_content = format_results_for_github(results_df, system_info, categories)
         upload_to_github(markdown_content, plot_files, github_auth, results_df, system_info, categories)
     end