fix(docs): resolve markdown lint and link errors

- auto-fix blanks-around-lists and blanks-around-fences violations
- add LICENSE.md and ISSUE_TEMPLATE.md to lint ignores
- fix line length and emphasis-as-heading in README
- update Azure CLI URL to learn.microsoft.com

📝 - Generated by Copilot

Author: WilliamBerryiii

.github/ISSUE_TEMPLATE.md

@@ -1,10 +1,11 @@
 <!--
 IF SUFFICIENT INFORMATION IS NOT PROVIDED VIA THE FOLLOWING TEMPLATE THE ISSUE MIGHT BE CLOSED WITHOUT FURTHER CONSIDERATION OR INVESTIGATION
 -->
-> Please provide us with the following information:
+> Please provide us with the following information
 > ---------------------------------------------------------------
 
 ### This issue is for a: (mark with an `x`)
+
 ```
 - [ ] bug report -> please search issues before submitting
 - [ ] feature request
@@ -22,6 +23,7 @@ IF SUFFICIENT INFORMATION IS NOT PROVIDED VIA THE FOLLOWING TEMPLATE THE ISSUE M
 >
 
 ### OS and Version?
+>
 > Windows 7, 8 or 10. Linux (which distribution). macOS (Yosemite? El Capitan? Sierra?)
 
 ### Versions

.github/copilot-instructions.md

@@ -13,20 +13,24 @@ Items in **HIGHEST PRIORITY** sections from attached instructions files override
 **Artifacts:** Do not create or modify tests, scripts, or one-off markdown docs unless explicitly requested.
 
 **Comment policy:** Never include thought processes, step-by-step reasoning, or narrative comments in code.
+
 * Keep comments brief and factual; describe **behavior/intent, invariants, edge cases**.
 * Remove or update comments that contradict the current behavior. Do not restate obvious functionality.
 * Do NOT add temporal or plan-phase markers (e.g. "Phase 1 cleanup", "... after migration", dates, or task references) to code files. When editing or updating any code files, always remove or replace these types of comments.
 
 **Conventions and Styling:** Always follow conventions and styling in this codebase FIRST for all changes, edits, updates, and new files.
+
 * Conventions and styling are in instruction files and must be read in with the `read_file` tool if not already added as an `<attachment>`.
 
 **Proactive fixes:** Always fix problems and errors you encounter, even if unrelated to the original request. Prefer root-cause, constructive fixes over symptom-only patches.
+
 * Always correct all incorrect or problematic conventions, styling, and redundant and/or misleading comments.
 
 **Deleting files and folders:** Use `rm` with the run_in_terminal tool when needing to delete files or folders.
 
 **Edit tools:** Never use `insert_edit_into_file` tool when other edit and file modification tools are available.
 
 **Memory and tracking work**: Always track work in Beads instead of Markdown.
+
 * All upcoming work, tracked work, issues, plans, todos, phases, tasks, and memory must always use the mcp_beads tools.
 * Don't ever use git commands for anything related to the mcp_beads tools and beads in general, its at the user's discretion when to use git commands and tools.

.github/instructions/commit-message.instructions.md

@@ -38,7 +38,6 @@ Scopes MUST be one of the following:
 - `(src)`
 - `(deploy)`
 
-
 ## Description
 
 - Description MUST be short and LESS THAN 100 bytes
@@ -62,7 +61,7 @@ For larger changes only:
 
 - Footer MUST start with a blank line
 - Must include an emoji that represents the change
-- Must end with ` - Generated by Copilot`
+- Must end with `- Generated by Copilot`
 
 ## Example Complete Commit Message - Large
 

.markdownlint-cli2.jsonc

@@ -2,7 +2,9 @@
   "ignores": [
     "**/node_modules/**",
     ".copilot-tracking/**",
-    "venv/**"
+    "venv/**",
+    "LICENSE.md",
+    ".github/ISSUE_TEMPLATE.md"
   ],
   "config": {
     "default": true,

LICENSE.md

@@ -18,4 +18,4 @@
     AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
     LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
     OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-    SOFTWARE
+    SOFTWARE

README.md

@@ -1,6 +1,7 @@
 # 🤖 Azure Robotics Reference Architecture with NVIDIA OSMO
 
-This reference architecture provides a production-ready framework for orchestrating robotics and AI workloads on [Microsoft Azure](https://azure.microsoft.com/) using NVIDIA technologies such as [Isaac Lab](https://developer.nvidia.com/isaac/lab), [Isaac Sim](https://developer.nvidia.com/isaac/sim), and [OSMO](https://developer.nvidia.com/osmo). It demonstrates end-to-end reinforcement learning workflows, scalable training pipelines, and deployment processes with Azure-native authentication, storage, and ML services.
+This reference architecture provides a production-ready framework for orchestrating robotics and AI workloads on [Microsoft Azure](https://azure.microsoft.com/) using NVIDIA technologies such as [Isaac Lab](https://developer.nvidia.com/isaac/lab), [Isaac Sim](https://developer.nvidia.com/isaac/sim), and [OSMO](https://developer.nvidia.com/osmo).
+It demonstrates end-to-end reinforcement learning workflows, scalable training pipelines, and deployment processes with Azure-native authentication, storage, and ML services.
 
 ## 🚀 Key Features
 
@@ -10,10 +11,10 @@ OSMO handles workflow orchestration and job scheduling while Azure provides elas
 - **Containerized Workflows** - Docker-based Isaac Lab training with NVIDIA GPU support
 - **CI/CD Integration** - Automated deployment pipelines with GitHub Actions
 - **MLflow Integration** - Automatic experiment tracking and model versioning
-    - Automatic metric logging from SKRL agents to Azure ML
-    - Comprehensive tracking of episode statistics, losses, optimization metrics, and timing data
-    - Configurable logging intervals and metric filtering
-    - See [MLflow Integration Guide](docs/mlflow-integration.md) for details
+  - Automatic metric logging from SKRL agents to Azure ML
+  - Comprehensive tracking of episode statistics, losses, optimization metrics, and timing data
+  - Configurable logging intervals and metric filtering
+  - See [MLflow Integration Guide](docs/mlflow-integration.md) for details
 - **Scalable Compute** - Auto-scaling GPU nodes based on workload demands
 - **Cost Optimization** - Pay-per-use compute with automatic scaling
 - **Enterprise Security** - Entra ID integration
@@ -22,6 +23,7 @@ OSMO handles workflow orchestration and job scheduling while Azure provides elas
 ## 🗼 Architecture Overview
 
 This reference architecture integrates:
+
 - **NVIDIA OSMO** - Workflow orchestration and job scheduling
 - **Azure Machine Learning** - Experiment tracking and model management
 - **Azure Kubernetes Service** - Software in the Loop (SIL) training
@@ -30,7 +32,7 @@ This reference architecture integrates:
 - **Azure Key Vault** - Secure credential management
 - **Azure Monitor** - Comprehensive logging and metrics
 
-**INSERT ARCHITECTURE DIAGRAM HERE**
+<!-- INSERT ARCHITECTURE DIAGRAM HERE -->
 
 ## 🌍 Real World Examples
 
@@ -49,17 +51,19 @@ See [OSMO workflow examples](deploy/004-workflow/osmo/) for job configuration te
 
 - [pyenv](https://github.com/pyenv/pyenv)
 - Python 3.11 (required by Isaac Sim 5.X)
-- [Azure CLI](https://docs.microsoft.com/en-us/cli/azure/install-azure-cli) (v2.50+)
+- [Azure CLI](https://learn.microsoft.com/cli/azure/install-azure-cli) (v2.50+)
 - [Terraform](https://www.terraform.io/downloads) (v1.5+)
 - [NVIDIA OSMO CLI](https://developer.nvidia.com/osmo) (latest)
 - [Docker](https://docs.docker.com/get-docker/) with NVIDIA Container Toolkit
 
 ### Azure Requirements
+
 - Azure subscription with contributor access
 - Sufficient quota for GPU VMs (Standard_NC6s_v3 or higher)
 - Azure Machine Learning workspace (or permissions to create one)
 
 ### NVIDIA Requirements
+
 - NVIDIA Developer account with OSMO access
 - NGC API key for container registry access
 
@@ -112,14 +116,14 @@ This project is licensed under the MIT License. See [LICENSE.md](LICENSE.md) for
 
 For issues and questions:
 
-* Review [microsoft/edge-ai](https://github.com/microsoft/edge-ai) documentation
+- Review [microsoft/edge-ai](https://github.com/microsoft/edge-ai) documentation
 
 ## 🙏 Acknowledgments
 
 This reference architecture builds upon:
 
-* [microsoft/edge-ai](https://github.com/microsoft/edge-ai) - Edge AI infrastructure components
-* [NVIDIA Isaac Lab](https://github.com/isaac-sim/IsaacLab) - RL task framework
-* [NVIDIA Isaac Sim](https://developer.nvidia.com/isaac-sim) - Physics simulation
-* [NVIDIA OSMO](https://developer.nvidia.com/osmo) - Workflow orchestration
-* [NVIDIA OSMO GitHub](https://github.com/NVIDIA/OSMO) - Workflow orchestration
+- [microsoft/edge-ai](https://github.com/microsoft/edge-ai) - Edge AI infrastructure components
+- [NVIDIA Isaac Lab](https://github.com/isaac-sim/IsaacLab) - RL task framework
+- [NVIDIA Isaac Sim](https://developer.nvidia.com/isaac-sim) - Physics simulation
+- [NVIDIA OSMO](https://developer.nvidia.com/osmo) - Workflow orchestration
+- [NVIDIA OSMO GitHub](https://github.com/NVIDIA/OSMO) - Workflow orchestration