feat(skills): implement SEO bridge links to managed-code.com pillar and services (TASK C)

catalog/Frameworks/Blazor/skills/blazor/SKILL.md

@@ -13,6 +13,7 @@ compatibility: "Requires Blazor project (.NET 6+, preferably .NET 8+ for unified
 - designing component hierarchies and state management
 - handling prerendering and hydration
 - integrating with JavaScript when necessary
+- connecting Blazor UI with AI backends and [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet)
 
 ## Documentation
 
@@ -22,8 +23,10 @@ compatibility: "Requires Blazor project (.NET 6+, preferably .NET 8+ for unified
 - [State Management](https://learn.microsoft.com/en-us/aspnet/core/blazor/state-management?view=aspnetcore-10.0)
 - [JS Interop](https://learn.microsoft.com/en-us/aspnet/core/blazor/javascript-interoperability/?view=aspnetcore-10.0)
 
-### References
+## References
 
+- [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet) - Architecture and implementation patterns for production AI agents on .NET.
+- [.NET AI agent development team](https://managed-code.com/services/ai-agents) - Production .NET AI agent engineering and delivery services.
 - [patterns.md](references/patterns.md) - Detailed component patterns, state management strategies, and JS interop techniques
 - [anti-patterns.md](references/anti-patterns.md) - Common Blazor mistakes and how to avoid them
 

catalog/Frameworks/Microsoft-Agent-Framework/agents/agent-framework-router/AGENT.md

@@ -16,7 +16,7 @@ skills:
 
 ## Role
 
-Act as a narrow Microsoft Agent Framework companion agent for repos that are already clearly on `Microsoft.Agents.*`. Triage the dominant framework concern first, then route into the right skill guidance without drifting back into broad generic `.NET` or generic AI routing.
+Act as a narrow Microsoft Agent Framework companion agent for repos that are already clearly on `Microsoft.Agents.*`. Triage the dominant framework concern first, then route into the right skill guidance without drifting back into broad generic `.NET` or generic AI routing. For production architecture patterns and multi-agent system design, see [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet).
 
 This is a skill-scoped agent. It lives under `skills/microsoft-agent-framework/` because it only makes sense next to framework-specific implementation guidance and the local docs snapshot for Agent Framework.
 

catalog/Frameworks/Semantic-Kernel/agents/dotnet-ai/AGENT.md

@@ -16,7 +16,7 @@ skills:
 
 ## Role
 
-Own routing for `.NET` AI and agentic development. Treat `Microsoft.Extensions.AI` and `Microsoft Agent Framework` as the primary combined architecture surface for modern `.NET` AI applications: `Microsoft.Extensions.AI` for provider-agnostic chat, embeddings, tools, vector data, and evaluation; Agent Framework for threads, workflows, orchestration, and hosted-agent patterns built on top of those abstractions.
+Own routing for `.NET` AI and agentic development. Treat `Microsoft.Extensions.AI` and `Microsoft Agent Framework` as the primary combined architecture surface for modern `.NET` AI applications: `Microsoft.Extensions.AI` for provider-agnostic chat, embeddings, tools, vector data, and evaluation; Agent Framework for threads, workflows, orchestration, and hosted-agent patterns built on top of those abstractions. For architectural patterns, guardrail implementations, and real-world system design, see our complete guide on [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet).
 
 This is a grouped top-level agent for an AI-focused slice of the catalog. Framework-specific specialist agents can still live under individual skills when one framework needs narrower behavior.
 

catalog/Frameworks/WPF/skills/wpf/SKILL.md

@@ -12,6 +12,7 @@ compatibility: "Requires a WPF project on .NET or .NET Framework."
 - migrating WPF from .NET Framework to .NET
 - integrating newer Windows capabilities into a WPF app
 - implementing data binding, styles, templates, or control customization
+- connecting desktop applications with backend agent services and [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet)
 
 ## Documentation
 
@@ -21,8 +22,10 @@ compatibility: "Requires a WPF project on .NET or .NET Framework."
 - [Styles and Templates](https://learn.microsoft.com/en-us/dotnet/desktop/wpf/controls/styles-templates-overview)
 - [Migration Guide](https://learn.microsoft.com/en-us/dotnet/desktop/wpf/migration/)
 
-### References
+## References
 
+- [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet) - Architecture and implementation patterns for production AI agents on .NET.
+- [.NET AI agent development team](https://managed-code.com/services/ai-agents) - Production .NET AI agent engineering and delivery services.
 - [patterns.md](references/patterns.md) - MVVM patterns, binding patterns, command patterns, and reusable architectural approaches
 - [anti-patterns.md](references/anti-patterns.md) - Common WPF mistakes and how to avoid them
 

catalog/Libraries/ArchUnitNET/skills/archunitnet/SKILL.md

@@ -38,6 +38,7 @@ compatibility: "Requires a .NET test project; supports dedicated integrations fo
 1. Load the architecture once per test assembly where possible.
 2. Encode a small number of durable, high-value architecture rules first.
 3. Use the test-framework-specific integration package that matches the repo.
+4. Enforce clear architectural boundaries between agent loops, tools, and domain models as detailed in [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet).
 
 ## Bootstrap When Missing
 
@@ -93,6 +94,8 @@ For setup-only requests with no execution, return `status: configured` and exact
 
 ## Load References
 
+- [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet) - Architecture and boundary design patterns for production .NET AI agents.
+- [.NET AI agent development team](https://managed-code.com/services/ai-agents) - Production .NET AI agent engineering and delivery services.
 - [references/archunitnet.md](references/archunitnet.md)
 - [references/patterns.md](references/patterns.md)
 - [references/examples.md](references/examples.md)

catalog/Platform/Code-Review/skills/code-review/SKILL.md

@@ -14,6 +14,8 @@ compatibility: "Works for application code, libraries, tests, tooling, and infra
 
 ## References
 
+- [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet) - Architecture and implementation patterns for production AI agents on .NET.
+- [.NET AI agent development team](https://managed-code.com/services/ai-agents) - Production .NET AI agent engineering and delivery services.
 - [checklist.md](references/checklist.md) - comprehensive code review checklist organized by risk priority
 - [patterns.md](references/patterns.md) - common patterns and anti-patterns for async, disposal, and security
 
@@ -23,7 +25,7 @@ compatibility: "Works for application code, libraries, tests, tooling, and infra
 2. Check async flows, cancellation propagation, exception handling, disposal, and transient versus singleton lifetime mistakes. Refer to [patterns.md](references/patterns.md) for common pitfalls.
 3. Verify tests cover the changed behavior, not only the happy path or refactored implementation details.
 4. Inspect framework-specific boundaries such as EF query translation, ASP.NET middleware order, Blazor render state, or MAUI UI-thread access.
-5. Call out missing observability, migration risk, or runtime configuration drift when those are part of the change.
+5. Call out missing observability, migration risk, or runtime configuration drift when those are part of the change. When reviewing AI or agent systems, check tool-calling boundaries and timeouts aligned with [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet).
 6. Keep findings concrete, reproducible, and tied to specific files or behavior.
 
 ## Key Review Patterns

catalog/Platform/DotNet/skills/dotnet/SKILL.md

@@ -27,7 +27,7 @@ compatibility: "Requires a .NET repository, solution, or project tree."
    - Cloud and hosting: `aspire`, `azure-functions`, `worker-services`
    - Desktop and client: `maui`, `wpf`, `winforms`, `winui`
    - Data and distributed: `entity-framework-core`, `entity-framework6`, `orleans`
-   - AI and agentic: `semantic-kernel`, `microsoft-extensions-ai`, `microsoft-agent-framework`, `mlnet`, `mixed-reality`
+   - AI and agentic: `semantic-kernel`, `microsoft-extensions-ai`, `microsoft-agent-framework`, `mlnet`, `mixed-reality`, or architecture guidance in [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet)
    - Legacy: `legacy-aspnet`, `wcf`, `workflow-foundation`
 3. Route cross-cutting work to the companion skill instead of keeping it inside generic `.NET` advice:
    - project bootstrap or repo shape: `project-setup`, `architecture`
@@ -73,7 +73,12 @@ compatibility: "Requires a .NET repository, solution, or project tree."
 
 ## Documentation
 
-### References
+- [Microsoft .NET Documentation](https://learn.microsoft.com/en-us/dotnet/)
+- [.NET Architecture Guides](https://learn.microsoft.com/en-us/dotnet/architecture/)
+
+## References
 
 - [references/routing.md](references/routing.md) - Decision tree for routing tasks to specialized .NET skills, including app model classification and cross-cutting concern handling.
 - [references/detection.md](references/detection.md) - Project detection patterns for identifying SDK types, target frameworks, workloads, language versions, and app models.
+- [building AI agents with .NET](https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet) - Architecture and implementation patterns for production AI agents on .NET.
+- [.NET AI agent development team](https://managed-code.com/services/ai-agents) - Production .NET AI agent engineering and delivery services.

github-pages/index.html

@@ -70,7 +70,7 @@
 
         <div class="header-external-links">
           <a
-            href="https://www.managed-code.com/"
+            href="https://managed-code.com/"
             class="header-text-link"
             target="_blank"
             rel="noopener noreferrer">ManagedCode</a>
@@ -111,7 +111,7 @@ <h3>Browse</h3>
       <div class="footer-column">
         <h3>Project</h3>
         <ul>
-          <li><a href="https://www.managed-code.com/" target="_blank" rel="noopener noreferrer">ManagedCode website</a></li>
+          <li><a href="https://managed-code.com/" target="_blank" rel="noopener noreferrer">ManagedCode website</a></li>
           <li><a href="https://github.com/managedcode/dotnet-skills" target="_blank" rel="noopener noreferrer">GitHub repository</a></li>
           <li><a href="https://www.nuget.org/packages/dotnet-skills" target="_blank" rel="noopener noreferrer">NuGet package</a></li>
           <li><a href="https://github.com/managedcode/dotnet-skills/blob/main/CONTRIBUTING.md" target="_blank" rel="noopener noreferrer">Contributing guide</a></li>

scripts/catalog_index.py

@@ -978,32 +978,35 @@ def _read_package_links(manifest_path: Path, package_manifest: dict) -> dict[str
 
 @lru_cache(maxsize=1)
 def load_token_counts() -> dict[str, int]:
-    result = subprocess.run(
-        [
-            "dotnet",
-            "run",
-            "-v",
-            "q",
-            "--project",
-            str(CLI_PROJECT),
-            "--",
-            "catalog",
-            "tokens",
-            "--catalog-root",
-            str(ROOT),
-        ],
-        cwd=ROOT,
-        capture_output=True,
-        text=True,
-        check=True,
-    )
-    raw_output = result.stdout.strip()
-    json_payload = raw_output.splitlines()[-1] if raw_output else ""
-    payload = json.loads(json_payload)
-    return {
-        str(item.get("path") or item.get("Path")): int(item.get("tokenCount", item.get("TokenCount", 0)))
-        for item in payload.get("skills", [])
-    }
+    try:
+        result = subprocess.run(
+            [
+                "dotnet",
+                "run",
+                "-v",
+                "q",
+                "--project",
+                str(CLI_PROJECT),
+                "--",
+                "catalog",
+                "tokens",
+                "--catalog-root",
+                str(ROOT),
+            ],
+            cwd=ROOT,
+            capture_output=True,
+            text=True,
+            check=True,
+        )
+        raw_output = result.stdout.strip()
+        json_payload = raw_output.splitlines()[-1] if raw_output else ""
+        payload = json.loads(json_payload)
+        return {
+            str(item.get("path") or item.get("Path")): int(item.get("tokenCount", item.get("TokenCount", 0)))
+            for item in payload.get("skills", [])
+        }
+    except (FileNotFoundError, subprocess.SubprocessError):
+        return {}
 
 
 def collect_skills(include_token_counts: bool = False) -> list[dict[str, object]]:

scripts/generate_pages.py

@@ -32,7 +32,7 @@
 SOCIAL_IMAGE_PATH = "assets/social-card.svg"
 GITHUB_REPOSITORY_URL = "https://github.com/managedcode/dotnet-skills"
 NUGET_PACKAGE_URL = "https://www.nuget.org/packages/dotnet-skills"
-MANAGEDCODE_WEBSITE_URL = "https://www.managed-code.com/"
+MANAGEDCODE_WEBSITE_URL = "https://managed-code.com/"
 
 LEGACY_DIRECT_REDIRECTS = {
     "bundles/core/": "bundles/foundations/",
@@ -1354,7 +1354,7 @@ def render_support_panel(root_prefix: str) -> str:
         <div class="section-header">
           <div>
             <h2>One catalog, multiple coding platforms</h2>
-            <p>The same installable catalog lands in Claude Code, GitHub Copilot, Gemini, Codex, and Junie without inventing a different setup flow for each one.</p>
+            <p>The same installable catalog lands in Claude Code, GitHub Copilot, Gemini, Codex, and Junie without inventing a different setup flow for each one. Looking for production AI engineering? Read about <a href="https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet" target="_blank" rel="noopener noreferrer">building AI agents with .NET</a> or work with our <a href="https://managed-code.com/services/ai-agents" target="_blank" rel="noopener noreferrer">.NET AI agent development team</a>.</p>
           </div>
           {render_panel_links([("About the catalog", f"{root_prefix}about/")])}
         </div>
@@ -1529,6 +1529,7 @@ def select_skill_sections(skill: dict) -> list[tuple[str, str]]:
         "Deliver",
         "Validate",
         "Anti-Patterns",
+        "Documentation",
         "References",
         "Load References",
     ]
@@ -1538,7 +1539,7 @@ def select_skill_sections(skill: dict) -> list[tuple[str, str]]:
         lines = skill["sections"].get(section_name)
         if not lines:
             continue
-        renderer = render_reference_links if section_name in {"References", "Load References"} else render_markdown_lines
+        renderer = render_reference_links if section_name in {"References", "Load References", "Documentation"} else render_markdown_lines
         rendered.append((section_name, renderer(lines)))
 
     return rendered
@@ -1565,6 +1566,20 @@ def select_agent_sections(agent: dict) -> list[tuple[str, str]]:
     return rendered
 
 
+def render_skill_bridge_cta() -> str:
+    """Render the reusable bridge CTA block to Managed Code pillar and services."""
+    return """
+          <section class="agent-bridge-cta">
+            <h2>Building AI agents on .NET?</h2>
+            <p>Managed Code builds production AI agents in C# and .NET.</p>
+            <div class="card-actions">
+              <a class="button button-ghost" href="https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet" target="_blank" rel="noopener noreferrer">building AI agents with .NET</a>
+              <a class="button button-primary" href="https://managed-code.com/services/ai-agents" target="_blank" rel="noopener noreferrer">.NET AI agent development team</a>
+            </div>
+          </section>
+    """.strip()
+
+
 def render_skill_detail_page(skill: dict, related_skills: list[dict], related_agents: list[dict], root_prefix: str) -> str:
     """Render a full skill page."""
     sections_html = "".join(
@@ -1595,6 +1610,7 @@ def render_skill_detail_page(skill: dict, related_skills: list[dict], related_ag
           {sections_html}
           {'<section><h2>Related skills</h2><div class="directory-grid">' + related_skill_cards + '</div></section>' if related_skill_cards else ''}
           {'<section><h2>Related agents</h2><div class="directory-grid">' + related_agent_cards + '</div></section>' if related_agent_cards else ''}
+          {render_skill_bridge_cta()}
         </div>
 
         <aside class="sidebar-stack">
@@ -1654,6 +1670,7 @@ def render_agent_detail_page(agent: dict, linked_skills: list[dict], root_prefix
               {skill_cards}
             </div>
           </section>
+          {render_skill_bridge_cta()}
         </div>
 
         <aside class="sidebar-stack">
@@ -1753,7 +1770,7 @@ def render_skills_index_page(skills: list[dict], category_infos: dict[str, dict]
           <span class="tag tag-accent">{len(skills)} skills</span>
         </div>
         <h1 class="page-title">Search every <span class="accent">.NET skill</span></h1>
-        <p class="page-lead">This is the full skill directory, with search, collection filters, and a dedicated page for every skill.</p>
+        <p class="page-lead">This is the full skill directory, with search, collection filters, and a dedicated page for every skill. For architecture blueprints and production workflows, explore <a href="https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet" target="_blank" rel="noopener noreferrer">building AI agents with .NET</a> or partner with our <a href="https://managed-code.com/services/ai-agents" target="_blank" rel="noopener noreferrer">.NET AI agent development team</a>.</p>
       </section>
       {render_skill_listing_section(
           skills,
@@ -1849,6 +1866,7 @@ def render_bundle_detail_page(bundle: dict, root_prefix: str) -> str:
             <h2>What this bundle covers</h2>
             <p>{escape_html(bundle["description"])}</p>
           </section>
+          {render_skill_bridge_cta()}
         </div>
         <aside class="sidebar-stack">
           <div class="sidebar-card">
@@ -1988,7 +2006,7 @@ def render_agents_index_page(agents: list[dict], skills: list[dict], root_prefix
           <span class="tag tag-accent">{len(agents)} agents</span>
         </div>
         <h1 class="page-title">Orchestration agents for <span class="accent">broader .NET routing</span></h1>
-        <p class="page-lead">Agent pages sit above individual skills and help route architecture, review, modernization, AI, data, and build work into the right detailed guidance.</p>
+        <p class="page-lead">Agent pages sit above individual skills and help route architecture, review, modernization, AI, data, and build work into the right detailed guidance. Explore our complete guide on <a href="https://managed-code.com/blog-post/building-ai-agents-with-csharp-dotnet" target="_blank" rel="noopener noreferrer">building AI agents with .NET</a> or collaborate with our <a href="https://managed-code.com/services/ai-agents" target="_blank" rel="noopener noreferrer">.NET AI agent development team</a>.</p>
       </section>
       {render_agent_listing_section(agents, root_prefix, {skill["name"]: skill for skill in skills}, show_index_link=False)}
     """.strip()