chore: sync Arize skills from arize-skills@597d609bfe5f07fd7d24acfdb408a082911b18fc and phoenix@746247cbb07b0dc7803b87c69dd8c77811c33f59 (#1583)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

docs/README.skills.md

@@ -43,14 +43,14 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to
 | [architecture-blueprint-generator](../skills/architecture-blueprint-generator/SKILL.md)<br />`gh skills install github/awesome-copilot architecture-blueprint-generator` | Comprehensive project architecture blueprint generator that analyzes codebases to create detailed architectural documentation. Automatically detects technology stacks and architectural patterns, generates visual diagrams, documents implementation patterns, and provides extensible blueprints for maintaining architectural consistency and guiding new development. | None |
 | [arduino-azure-iot-edge-integration](../skills/arduino-azure-iot-edge-integration/SKILL.md)<br />`gh skills install github/awesome-copilot arduino-azure-iot-edge-integration` | Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails. | `references/arduino-iot-checklist.md`<br />`references/arduino-official-best-practices.md` |
 | [arize-ai-provider-integration](../skills/arize-ai-provider-integration/SKILL.md)<br />`gh skills install github/awesome-copilot arize-ai-provider-integration` | INVOKE THIS SKILL when creating, reading, updating, or deleting Arize AI integrations. Covers listing integrations, creating integrations for any supported LLM provider (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, custom), updating credentials or metadata, and deleting integrations using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
-| [arize-annotation](../skills/arize-annotation/SKILL.md)<br />`gh skills install github/awesome-copilot arize-annotation` | INVOKE THIS SKILL when creating, managing, or using annotation configs on Arize (categorical, continuous, freeform), or applying human annotations to project spans via the Python SDK. Configs are the label schema for human feedback on spans and other surfaces in the Arize UI. Triggers: annotation config, label schema, human feedback schema, bulk annotate spans, update_annotations. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
-| [arize-dataset](../skills/arize-dataset/SKILL.md)<br />`gh skills install github/awesome-copilot arize-dataset` | INVOKE THIS SKILL when creating, managing, or querying Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
+| [arize-annotation](../skills/arize-annotation/SKILL.md)<br />`gh skills install github/awesome-copilot arize-annotation` | INVOKE THIS SKILL when creating, managing, or using annotation configs or annotation queues on Arize (categorical, continuous, freeform), or applying human annotations to project spans via the Python SDK. Configs are the label schema for human feedback; queues are review workflows that route records to annotators. Triggers: annotation config, annotation queue, label schema, human feedback schema, bulk annotate spans, update_annotations, labeling queue, annotate record. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
+| [arize-dataset](../skills/arize-dataset/SKILL.md)<br />`gh skills install github/awesome-copilot arize-dataset` | INVOKE THIS SKILL when creating, managing, or querying Arize datasets and examples. Also use when the user needs test data or evaluation examples for their model. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
 | [arize-evaluator](../skills/arize-evaluator/SKILL.md)<br />`gh skills install github/awesome-copilot arize-evaluator` | INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
-| [arize-experiment](../skills/arize-experiment/SKILL.md)<br />`gh skills install github/awesome-copilot arize-experiment` | INVOKE THIS SKILL when creating, running, or analyzing Arize experiments. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
-| [arize-instrumentation](../skills/arize-instrumentation/SKILL.md)<br />`gh skills install github/awesome-copilot arize-instrumentation` | INVOKE THIS SKILL when adding Arize AX tracing to an application. Follow the Agent-Assisted Tracing two-phase flow: analyze the codebase (read-only), then implement instrumentation after user confirmation. When the app uses LLM tool/function calling, add manual CHAIN + TOOL spans so traces show each tool's input and output. Leverages https://arize.com/docs/ax/alyx/tracing-assistant and https://arize.com/docs/PROMPT.md. | `references/ax-profiles.md` |
-| [arize-link](../skills/arize-link/SKILL.md)<br />`gh skills install github/awesome-copilot arize-link` | Generate deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config. | `references/EXAMPLES.md` |
-| [arize-prompt-optimization](../skills/arize-prompt-optimization/SKILL.md)<br />`gh skills install github/awesome-copilot arize-prompt-optimization` | INVOKE THIS SKILL when optimizing, improving, or debugging LLM prompts using production trace data, evaluations, and annotations. Covers extracting prompts from spans, gathering performance signal, and running a data-driven optimization loop using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
-| [arize-trace](../skills/arize-trace/SKILL.md)<br />`gh skills install github/awesome-copilot arize-trace` | INVOKE THIS SKILL when downloading or exporting Arize traces and spans. Covers exporting traces by ID, sessions by ID, and debugging LLM application issues using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
+| [arize-experiment](../skills/arize-experiment/SKILL.md)<br />`gh skills install github/awesome-copilot arize-experiment` | INVOKE THIS SKILL when creating, running, or analyzing Arize experiments. Also use when the user wants to evaluate or measure model performance, compare models (including GPT-4, Claude, or others), or assess how well their AI is doing. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
+| [arize-instrumentation](../skills/arize-instrumentation/SKILL.md)<br />`gh skills install github/awesome-copilot arize-instrumentation` | INVOKE THIS SKILL when adding Arize AX tracing or observability to an app for the first time, or when the user wants to instrument their LLM app or get started with LLM observability. Follow the Agent-Assisted Tracing two-phase flow: analyze the codebase (read-only), then implement after user confirmation. When the app uses LLM tool/function calling, add manual CHAIN + TOOL spans. Leverages https://arize.com/docs/ax/alyx/tracing-assistant and https://arize.com/docs/PROMPT.md. | `references/ax-profiles.md` |
+| [arize-link](../skills/arize-link/SKILL.md)<br />`gh skills install github/awesome-copilot arize-link` | Generate deep links to the Arize UI. Use when the user wants a clickable URL to open or share a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config, or when sharing Arize resources with team members. | `references/EXAMPLES.md` |
+| [arize-prompt-optimization](../skills/arize-prompt-optimization/SKILL.md)<br />`gh skills install github/awesome-copilot arize-prompt-optimization` | INVOKE THIS SKILL when optimizing, improving, or debugging LLM prompts using production trace data, evaluations, and annotations. Also use when the user wants to make their AI respond better or improve AI output quality. Covers extracting prompts from spans, gathering performance signal, and running a data-driven optimization loop using the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
+| [arize-trace](../skills/arize-trace/SKILL.md)<br />`gh skills install github/awesome-copilot arize-trace` | INVOKE THIS SKILL when downloading, exporting, or inspecting Arize traces and spans, or when a user wants to look at what their LLM app is doing using existing trace data, or when an already-instrumented app has a bug or error to investigate. Use for debugging unknown runtime issues, failures, and behavior regressions. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation with the ax CLI. | `references/ax-profiles.md`<br />`references/ax-setup.md` |
 | [aspire](../skills/aspire/SKILL.md)<br />`gh skills install github/awesome-copilot aspire` | Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application. | `references/architecture.md`<br />`references/cli-reference.md`<br />`references/dashboard.md`<br />`references/deployment.md`<br />`references/integrations-catalog.md`<br />`references/mcp-server.md`<br />`references/polyglot-apis.md`<br />`references/testing.md`<br />`references/troubleshooting.md` |
 | [aspnet-minimal-api-openapi](../skills/aspnet-minimal-api-openapi/SKILL.md)<br />`gh skills install github/awesome-copilot aspnet-minimal-api-openapi` | Create ASP.NET Minimal API endpoints with proper OpenAPI documentation | None |
 | [audit-integrity](../skills/audit-integrity/SKILL.md)<br />`gh skills install github/awesome-copilot audit-integrity` | Shared audit integrity framework for all AppSec agents — enforces output quality, intellectual honesty, and continuous improvement through anti-rationalization guards, self-critique loops, retry protocols, non-negotiable behaviors, self-reflection quality gates (1-10 scoring, ≥8 threshold), and a self-learning system with lesson/memory governance for security analysis agents. | `references/anti-rationalization-guard.md`<br />`references/clarification-protocol.md`<br />`references/non-negotiable-behaviors.md`<br />`references/retry-protocol.md`<br />`references/self-critique-loop.md`<br />`references/self-learning-system.md`<br />`references/self-reflection-quality-gate.md` |
@@ -241,9 +241,9 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to
 | [openapi-to-application-code](../skills/openapi-to-application-code/SKILL.md)<br />`gh skills install github/awesome-copilot openapi-to-application-code` | Generate a complete, production-ready application from an OpenAPI specification | None |
 | [pdftk-server](../skills/pdftk-server/SKILL.md)<br />`gh skills install github/awesome-copilot pdftk-server` | Skill for using the command-line tool pdftk (PDFtk Server) for working with PDF files. Use when asked to merge PDFs, split PDFs, rotate pages, encrypt or decrypt PDFs, fill PDF forms, apply watermarks, stamp overlays, extract metadata, burst documents into pages, repair corrupted PDFs, attach or extract files, or perform any PDF manipulation from the command line. | `references/download.md`<br />`references/pdftk-cli-examples.md`<br />`references/pdftk-man-page.md`<br />`references/pdftk-server-license.md`<br />`references/third-party-materials.md` |
 | [penpot-uiux-design](../skills/penpot-uiux-design/SKILL.md)<br />`gh skills install github/awesome-copilot penpot-uiux-design` | Comprehensive guide for creating professional UI/UX designs in Penpot using MCP tools. Use this skill when: (1) Creating new UI/UX designs for web, mobile, or desktop applications, (2) Building design systems with components and tokens, (3) Designing dashboards, forms, navigation, or landing pages, (4) Applying accessibility standards and best practices, (5) Following platform guidelines (iOS, Android, Material Design), (6) Reviewing or improving existing Penpot designs for usability. Triggers: "design a UI", "create interface", "build layout", "design dashboard", "create form", "design landing page", "make it accessible", "design system", "component library". | `references/accessibility.md`<br />`references/component-patterns.md`<br />`references/platform-guidelines.md`<br />`references/setup-troubleshooting.md` |
-| [phoenix-cli](../skills/phoenix-cli/SKILL.md)<br />`gh skills install github/awesome-copilot phoenix-cli` | Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, review experiments, inspect datasets, and query the GraphQL API. Use when debugging AI/LLM applications, analyzing trace data, working with Phoenix observability, or investigating LLM performance issues. | None |
+| [phoenix-cli](../skills/phoenix-cli/SKILL.md)<br />`gh skills install github/awesome-copilot phoenix-cli` | Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, structure trace review with open coding and axial coding, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user is analyzing traces or spans, investigating LLM/agent failures, deciding what to do after instrumenting an app, building failure taxonomies, choosing what evals to write, or asking "what's going wrong", "what kinds of mistakes", or "where do I focus" — even without naming a technique. | `references/axial-coding.md`<br />`references/open-coding.md` |
 | [phoenix-evals](../skills/phoenix-evals/SKILL.md)<br />`gh skills install github/awesome-copilot phoenix-evals` | Build and run evaluators for AI/LLM applications using Phoenix. | `references/axial-coding.md`<br />`references/common-mistakes-python.md`<br />`references/error-analysis-multi-turn.md`<br />`references/error-analysis.md`<br />`references/evaluate-dataframe-python.md`<br />`references/evaluators-code-python.md`<br />`references/evaluators-code-typescript.md`<br />`references/evaluators-custom-templates.md`<br />`references/evaluators-llm-python.md`<br />`references/evaluators-llm-typescript.md`<br />`references/evaluators-overview.md`<br />`references/evaluators-pre-built.md`<br />`references/evaluators-rag.md`<br />`references/experiments-datasets-python.md`<br />`references/experiments-datasets-typescript.md`<br />`references/experiments-overview.md`<br />`references/experiments-running-python.md`<br />`references/experiments-running-typescript.md`<br />`references/experiments-synthetic-python.md`<br />`references/experiments-synthetic-typescript.md`<br />`references/fundamentals-anti-patterns.md`<br />`references/fundamentals-model-selection.md`<br />`references/fundamentals.md`<br />`references/observe-sampling-python.md`<br />`references/observe-sampling-typescript.md`<br />`references/observe-tracing-setup.md`<br />`references/production-continuous.md`<br />`references/production-guardrails.md`<br />`references/production-overview.md`<br />`references/setup-python.md`<br />`references/setup-typescript.md`<br />`references/validation-evaluators-python.md`<br />`references/validation-evaluators-typescript.md`<br />`references/validation.md` |
-| [phoenix-tracing](../skills/phoenix-tracing/SKILL.md)<br />`gh skills install github/awesome-copilot phoenix-tracing` | OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production. | `references/annotations-overview.md`<br />`references/annotations-python.md`<br />`references/annotations-typescript.md`<br />`references/fundamentals-flattening.md`<br />`references/fundamentals-overview.md`<br />`references/fundamentals-required-attributes.md`<br />`references/fundamentals-universal-attributes.md`<br />`references/instrumentation-auto-python.md`<br />`references/instrumentation-auto-typescript.md`<br />`references/instrumentation-manual-python.md`<br />`references/instrumentation-manual-typescript.md`<br />`references/metadata-python.md`<br />`references/metadata-typescript.md`<br />`references/production-python.md`<br />`references/production-typescript.md`<br />`references/projects-python.md`<br />`references/projects-typescript.md`<br />`references/sessions-python.md`<br />`references/sessions-typescript.md`<br />`references/setup-python.md`<br />`references/setup-typescript.md`<br />`references/span-agent.md`<br />`references/span-chain.md`<br />`references/span-embedding.md`<br />`references/span-evaluator.md`<br />`references/span-guardrail.md`<br />`references/span-llm.md`<br />`references/span-reranker.md`<br />`references/span-retriever.md`<br />`references/span-tool.md` |
+| [phoenix-tracing](../skills/phoenix-tracing/SKILL.md)<br />`gh skills install github/awesome-copilot phoenix-tracing` | OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production. | `README.md`<br />`references/annotations-overview.md`<br />`references/annotations-python.md`<br />`references/annotations-typescript.md`<br />`references/fundamentals-flattening.md`<br />`references/fundamentals-overview.md`<br />`references/fundamentals-required-attributes.md`<br />`references/fundamentals-universal-attributes.md`<br />`references/instrumentation-auto-python.md`<br />`references/instrumentation-auto-typescript.md`<br />`references/instrumentation-manual-python.md`<br />`references/instrumentation-manual-typescript.md`<br />`references/metadata-python.md`<br />`references/metadata-typescript.md`<br />`references/production-python.md`<br />`references/production-typescript.md`<br />`references/projects-python.md`<br />`references/projects-typescript.md`<br />`references/sessions-python.md`<br />`references/sessions-typescript.md`<br />`references/setup-python.md`<br />`references/setup-typescript.md`<br />`references/span-agent.md`<br />`references/span-chain.md`<br />`references/span-embedding.md`<br />`references/span-evaluator.md`<br />`references/span-guardrail.md`<br />`references/span-llm.md`<br />`references/span-reranker.md`<br />`references/span-retriever.md`<br />`references/span-tool.md` |
 | [php-mcp-server-generator](../skills/php-mcp-server-generator/SKILL.md)<br />`gh skills install github/awesome-copilot php-mcp-server-generator` | Generate a complete PHP Model Context Protocol server project with tools, resources, prompts, and tests using the official PHP SDK | None |
 | [planning-oracle-to-postgres-migration-integration-testing](../skills/planning-oracle-to-postgres-migration-integration-testing/SKILL.md)<br />`gh skills install github/awesome-copilot planning-oracle-to-postgres-migration-integration-testing` | Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation. | None |
 | [plantuml-ascii](../skills/plantuml-ascii/SKILL.md)<br />`gh skills install github/awesome-copilot plantuml-ascii` | Generate ASCII art diagrams using PlantUML text mode. Use when user asks to create ASCII diagrams, text-based diagrams, terminal-friendly diagrams, or mentions plantuml ascii, text diagram, ascii art diagram. Supports: Converting PlantUML diagrams to ASCII art, Creating sequence diagrams, class diagrams, flowcharts in ASCII format, Generating Unicode-enhanced ASCII art with -utxt flag | None |