Replace GitHub issue comments with gist-based telemetry

- Switch from problematic GitHub issue comments to public gists
- Gists are more reliable, easier to create, and perfect for data sharing
- Each benchmark run creates a timestamped gist with full results
- Users can search GitHub gists for 'LinearSolve autotune' to see community data
- Gists support markdown formatting and are easily discoverable
- Remove repo/issue_number parameters - no longer needed
- Update documentation to reflect gist-based community sharing

GitHub gists are much better suited for this use case than issue comments.
They're designed for sharing code/data snippets and have better API support.

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

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

Author: ChrisRackauckas

docs/src/tutorials/autotune.md

@@ -318,12 +318,14 @@ This is expected - arbitrary precision arithmetic is much slower than hardware f
 
 ## Community and Telemetry
 
-By default, autotune results are shared with the LinearSolve.jl community to help improve algorithm selection for everyone. The shared data includes:
+By default, autotune results are shared with the LinearSolve.jl community via public GitHub gists to help improve algorithm selection for everyone. The shared data includes:
 
 - System information (OS, CPU, core count, etc.)
 - Algorithm performance results
 - NO personal information or sensitive data
 
+Results are uploaded as public gists that can be easily searched and viewed by the community.
+
 ### GitHub Authentication for Telemetry
 
 When telemetry is enabled, the system will prompt you to set up GitHub authentication if not already configured:
@@ -333,7 +335,7 @@ When telemetry is enabled, the system will prompt you to set up GitHub authentic
 results = autotune_setup(telemetry = true)
 ```
 
-The system will wait for you to create and paste a GitHub token. This helps the community by sharing performance data across different hardware configurations.
+The system will wait for you to create and paste a GitHub token. This helps the community by sharing performance data across different hardware configurations via easily discoverable GitHub gists.
 
 **Interactive Setup:**
 The autotune process will show step-by-step instructions and wait for you to:

lib/LinearSolveAutotune/src/LinearSolveAutotune.jl

@@ -181,7 +181,7 @@ function autotune_setup(;
 
     # Upload telemetry if requested
     if telemetry && nrow(successful_results) > 0
-        @info "📤 Preparing telemetry data for sharing..."
+        @info "📤 Preparing telemetry data for community sharing..."
         markdown_content = format_results_for_github(results_df, system_info, categories)
         upload_to_github(markdown_content, plot_files, github_auth)
     end

lib/LinearSolveAutotune/src/telemetry.jl

@@ -325,14 +325,12 @@ function format_detailed_results_markdown(df::DataFrame)
 end
 
 """
-    upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dict}, auth; 
-                     repo="SciML/LinearSolve.jl", issue_number=669)
+    upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dict}, auth)
 
-Upload benchmark results to GitHub issue as a comment.
+Upload benchmark results to GitHub as a gist for community sharing.
 Requires a pre-authenticated GitHub.jl auth object.
 """
-function upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dict}, auth;
-        repo = "SciML/LinearSolve.jl", issue_number = 669)
+function upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dict}, auth)
 
     if auth === nothing
         @info "⚠️  No GitHub authentication available. Saving results locally instead of uploading."
@@ -345,39 +343,53 @@ function upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dic
         return
     end
 
-    @info "📤 Uploading results to GitHub issue #$issue_number in $repo"
+    @info "📤 Creating GitHub gist with benchmark results..."
 
     try
-
-        # Get the repository
-        repo_obj = GitHub.repo(repo)
-
-        # Create the comment content
-        comment_body = content
-
-        # Handle different plot file formats
+        # Create gist content
+        gist_content = content
+        
+        # Add plot file information to the gist
         if plot_files !== nothing
             if isa(plot_files, Tuple)
                 # Backward compatibility: single plot
                 png_file, pdf_file = plot_files
-                comment_body *= "\n\n**Note**: Benchmark plots have been generated locally as `$png_file` and `$pdf_file`."
+                gist_content *= "\n\n**Note**: Benchmark plots have been generated locally as `$png_file` and `$pdf_file`."
             elseif isa(plot_files, Dict)
                 # Multiple plots by element type
-                comment_body *= "\n\n**Note**: Benchmark plots have been generated locally:"
+                gist_content *= "\n\n**Note**: Benchmark plots have been generated locally:"
                 for (eltype, files) in plot_files
                     png_file, pdf_file = files
-                    comment_body *= "\n- $eltype: `$png_file` and `$pdf_file`"
+                    gist_content *= "\n- $eltype: `$png_file` and `$pdf_file`"
                 end
             end
         end
-
-        # Post the comment using the correct GitHub.jl API
-        GitHub.create_comment(repo_obj, issue_number; body = comment_body, auth = auth)
-
-        @info "✅ Successfully posted benchmark results to GitHub issue #$issue_number"
+        
+        # Create gist files dictionary
+        files = Dict{String, Dict{String, String}}()
+        timestamp = replace(string(Dates.now()), ":" => "-")
+        filename = "LinearSolve_autotune_$(timestamp).md"
+        files[filename] = Dict("content" => gist_content)
+        
+        # Create the gist
+        gist_data = Dict(
+            "description" => "LinearSolve.jl Autotune Benchmark Results - $(Dates.format(Dates.now(), "yyyy-mm-dd HH:MM"))",
+            "public" => true,
+            "files" => files
+        )
+        
+        # Use GitHub.jl to create gist
+        gist_result = GitHub.create_gist(gist_data; auth = auth)
+        
+        gist_url = gist_result.html_url
+        @info "✅ Successfully created GitHub gist: $gist_url"
+        @info "🔗 Your benchmark results are now available to help the LinearSolve.jl community!"
+        
+        # Also mention where to find community gists
+        @info "💡 To see other community benchmarks, search GitHub gists for 'LinearSolve autotune'"
 
     catch e
-        @warn "❌ Failed to upload to GitHub: $e"
+        @warn "❌ Failed to create GitHub gist: $e"
         @info "💡 This could be due to network issues, repository permissions, or API limits."
 
         # Save locally as fallback