Fix multiline descriptions in llms.txt to be single-line

Co-authored-by: aaronpowell <434140+aaronpowell@users.noreply.github.com>

eng/generate-llms-txt.mjs

@@ -47,18 +47,22 @@ function extractName(filePath, fileType) {
  * Extracts the description from a file's frontmatter
  * @param {string} filePath - Path to the file (or directory for skills)
  * @param {string} fileType - Type of file (agent, prompt, instruction, skill)
- * @returns {string} - The description of the resource
+ * @returns {string} - The description of the resource (single line)
  */
 function extractDescription(filePath, fileType) {
   try {
     if (fileType === "skill") {
       // For skills, filePath is the skill directory
       const skillMetadata = parseSkillMetadata(filePath);
-      return skillMetadata?.description || "No description available";
+      const description = skillMetadata?.description || "No description available";
+      // Convert multiline descriptions to single line
+      return description.replace(/\s+/g, " ").trim();
     }
 
     const frontmatter = parseFrontmatter(filePath);
-    return frontmatter?.description || "No description available";
+    const description = frontmatter?.description || "No description available";
+    // Convert multiline descriptions to single line
+    return description.replace(/\s+/g, " ").trim();
   } catch (error) {
     console.error(
       `Error extracting description from ${filePath}: ${error.message}`

llms.txt

@@ -22,7 +22,7 @@ This repository provides resources to customize and enhance GitHub Copilot:
 - [Address Comments](agents/address-comments.agent.md): Address PR comments
 - [ADR Generator](agents/adr-generator.agent.md): Expert agent for creating comprehensive Architectural Decision Records (ADRs) with structured formatting optimized for AI consumption and human readability.
 - [Aem Frontend Specialist](agents/aem-frontend-specialist.agent.md): Expert assistant for developing AEM components using HTL, Tailwind CSS, and Figma-to-code workflows with design system integration
-- [Amplitude Experiment Implementation](agents/amplitude-experiment-implementation.agent.md): This custom agent uses Amplitude's MCP tools to deploy new experiments inside of Amplitude, enabling seamless variant testing capabilities and rollout of product features.
+- [Amplitude Experiment Implementation](agents/amplitude-experiment-implementation.agent.md): This custom agent uses Amplitude's MCP tools to deploy new experiments inside of Amplitude, enabling seamless variant testing capabilities and rollout of product features.
 - [Api Architect](agents/api-architect.agent.md): Your role is that of an API architect. Help mentor the engineer by providing guidance, support, and working code.
 - [apify-integration-expert](agents/apify-integration-expert.agent.md): Expert agent for integrating Apify Actors into codebases. Handles Actor selection, workflow design, implementation across JavaScript/TypeScript and Python, testing, and production-ready deployment.
 - [Arch Linux Expert](agents/arch-linux-expert.agent.md): Arch Linux specialist focused on pacman, rolling-release maintenance, and Arch-centric system administration workflows.
@@ -473,13 +473,7 @@ This repository provides resources to customize and enhance GitHub Copilot:
 
 ## Skills
 
-- [agentic-eval](skills/agentic-eval): Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when:
+- [agentic-eval](skills/agentic-eval): Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
-- Implementing self-critique and reflection loops
-- Building evaluator-optimizer pipelines for quality-critical generation
-- Creating test-driven code refinement workflows
-- Designing rubric-based or LLM-as-judge evaluation systems
-- Adding iterative improvement to agent outputs (code, reports, analysis)
-- Measuring and improving agent response quality
 - [appinsights-instrumentation](skills/appinsights-instrumentation): Instrument a webapp to send useful telemetry data to Azure App Insights
 - [azure-deployment-preflight](skills/azure-deployment-preflight): Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.
 - [azure-devops-cli](skills/azure-devops-cli): Manage Azure DevOps resources via CLI including projects, repos, pipelines, builds, pull requests, work items, artifacts, and service endpoints. Use when working with Azure DevOps, az commands, devops automation, CI/CD, or when user mentions Azure DevOps CLI.