Fixing readme

Author: jimbobbennett

docs/README.skills.md

@@ -34,15 +34,15 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to
 | [apple-appstore-reviewer](../skills/apple-appstore-reviewer/SKILL.md) | Serves as a reviewer of the codebase with instructions on looking for Apple App Store optimizations or rejection reasons. | None |
 | [arch-linux-triage](../skills/arch-linux-triage/SKILL.md) | Triage and resolve Arch Linux issues with pacman, systemd, and rolling-release best practices. | None |
 | [architecture-blueprint-generator](../skills/architecture-blueprint-generator/SKILL.md) | 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 |
-| [arize-ai-provider-integration](../skills/arize-ai-provider-integration/SKILL.md) | 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. | `ax-profiles.md`<br />`ax-setup.md` |
-| [arize-annotation](../skills/arize-annotation/SKILL.md) | 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. | `ax-profiles.md`<br />`ax-setup.md` |
-| [arize-dataset](../skills/arize-dataset/SKILL.md) | 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. | `ax-profiles.md`<br />`ax-setup.md` |
-| [arize-evaluator](../skills/arize-evaluator/SKILL.md) | 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. | `ax-profiles.md`<br />`ax-setup.md` |
-| [arize-experiment](../skills/arize-experiment/SKILL.md) | INVOKE THIS SKILL when creating, running, or analyzing Arize experiments. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. | `ax-profiles.md`<br />`ax-setup.md` |
-| [arize-instrumentation](../skills/arize-instrumentation/SKILL.md) | 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. | `ax-profiles.md` |
-| [arize-link](../skills/arize-link/SKILL.md) | 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. | `EXAMPLES.md` |
-| [arize-prompt-optimization](../skills/arize-prompt-optimization/SKILL.md) | 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. | `ax-profiles.md`<br />`ax-setup.md` |
-| [arize-trace](../skills/arize-trace/SKILL.md) | 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. | `ax-profiles.md`<br />`ax-setup.md` |
+| [arize-ai-provider-integration](../skills/arize-ai-provider-integration/SKILL.md) | 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) | 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) | 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-evaluator](../skills/arize-evaluator/SKILL.md) | 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) | 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) | 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) | 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) | 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) | 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` |
 | [aspire](../skills/aspire/SKILL.md) | 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) | Create ASP.NET Minimal API endpoints with proper OpenAPI documentation | None |
 | [automate-this](../skills/automate-this/SKILL.md) | Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine. | None |
@@ -209,8 +209,8 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to
 | [pdftk-server](../skills/pdftk-server/SKILL.md) | 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) | 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) | 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-evals](../skills/phoenix-evals/SKILL.md) | Build and run evaluators for AI/LLM applications using Phoenix. | `rules` |
-| [phoenix-tracing](../skills/phoenix-tracing/SKILL.md) | OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production. | `README.md`<br />`rules` |
+| [phoenix-evals](../skills/phoenix-evals/SKILL.md) | 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) | 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) | 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) | 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) | 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 |