feat: add extract-feature and export-spec portability skills

Two new OpenSpec skills for porting features to sandboxed codebases:
- /opsx:extract-feature generates minimal, printable code recipes
- /opsx:export-spec generates compact specs for AI-assisted reimplementation
Both support cumulative dependency analysis across archived changes.

Includes first export of migrate-to-semantic-kernel in all three formats:
code recipe (~120 lines), portable spec (~40 lines), OpenSpec variant (~25 lines).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

openspec/exports/migrate-to-semantic-kernel-spec.md

@@ -0,0 +1,63 @@
+# Feature: SK Chat Endpoint with Tool Calling
+## Target: ApplicationX (ASP.NET Core + Blazor WASM + MudBlazor)
+
+**Included**: wire-responses-api (superseded — SK version used), migrate-to-semantic-kernel
+**Lines to type**: ~40 | **Code equivalent**: ~120 lines | **Compression**: 3x
+
+## Packages
+- Microsoft.SemanticKernel 1.74.0
+- Microsoft.SemanticKernel.Connectors.OpenAI 1.74.0
+
+## Architecture
+POST /api/chat accepts conversation messages, runs them through Semantic
+Kernel's chat completion with auto tool calling, streams response as SSE.
+An ExtractionPlugin lets the LLM validate structured data it extracts
+from natural language, retrying autonomously before escalating to the user.
+
+## Components
+
+### ChatController: Controllers/ChatController.cs
+- [ApiController] POST endpoint, injects Kernel via DI
+- Converts List<ChatMessage> to SK ChatHistory (user/assistant roles)
+- Imports ExtractionPlugin per-request via _kernel.ImportPluginFromObject
+- Uses OpenAIPromptExecutionSettings with FunctionChoiceBehavior.Auto()
+- Streams via GetStreamingChatMessageContentsAsync, skips empty chunks
+- SSE output: `data: {"text":"..."}\n\n` per chunk, `data: [DONE]\n\n` at end
+- Error: `data: {"error":"..."}\n\n` then [DONE]
+- Catches TaskCanceledException silently (client disconnect)
+
+### ExtractionPlugin: Plugins/ExtractionPlugin.cs
+- [KernelFunction("validate_extracted_fields")]
+- [Description] tells LLM: validates extracted fields against required schema
+- Accepts string fieldsJson, deserializes to ExtractedFields
+- Checks required fields non-null/non-empty, decimals > 0
+- Returns JSON: {"IsValid": bool, "Errors": ["..."]}
+
+### ExtractedFields: Shared/Models/ExtractedFields.cs
+- Required: Client(string?), Project(string?), Hours(decimal?), Rate(decimal?), Currency(string?), Date(string?)
+- Optional: Description(string?), PoNumber(string?)
+
+### ValidationResult: Shared/Models/ValidationResult.cs
+- IsValid(bool), Errors(List<string>)
+
+### ChatRequest + ChatMessage: Shared/Models/
+- ChatRequest: Messages(List<ChatMessage>)
+- ChatMessage: Role(string), Content(string), Timestamp(DateTime)
+
+## Wiring (Program.cs, after AddControllers)
+1. `using Microsoft.SemanticKernel;` at top (required for extension methods)
+2. Read BaseUrl and Model from config section "ResponsesApi"
+3. AddOpenAIChatCompletion(modelId, endpoint: new Uri(baseUrl), apiKey)
+4. AddKernel()
+5. AddSingleton<ExtractionPlugin>()
+6. CORS policy if Blazor client on different port
+
+## Config (appsettings.json)
+- ResponsesApi:BaseUrl = "http://localhost:8317/v1"
+- ResponsesApi:Model = "claude-sonnet-4-6"
+
+## Gotchas
+- Base URL MUST include /v1 — OpenAI SDK appends chat/completions directly
+- Plugin imported per-request, not at startup (avoids kernel state leaks)
+- SK has built-in auto-invoke limit — no need to set max retries
+- JsonSerializerOptions needs PropertyNameCaseInsensitive = true for deserialization