{BugFix} Project Aria Plugins - Fix markdown lint errors in ARK plugin SKILL.md files

Summary:
GitHub Actions `Markdown lint` job was failing with 11 errors across 6 SKILL.md files in `projectaria_ark_plugin/skills/`. All errors fall into three rules:

- **MD040** (fenced code blocks missing language): 6 fenced blocks containing ASCII diagrams, filesystem trees, and math formulas. Marked them as `text` so the lint rule passes without forcing syntax highlighting that wouldn't help readers.
- **MD012** (multiple consecutive blank lines): 1 stray double blank line in `aria-knowledge/SKILL.md` between the ALS section and the IMU noise model heading.
- **MD032** (lists not surrounded by blank lines): 4 list-after-paragraph instances in `client-sdk`, `mps`, and `projectaria-tools` SKILL.md — added the required blank line between the lead-in line and the first bullet.

No content changes — purely formatting to satisfy `markdownlint-cli2-action@v18` config in `.markdownlint.jsonc`.

Files touched:
- `projectaria_ark_plugin/skills/aria-knowledge/SKILL.md` (MD040 x2, MD012 x1)
- `projectaria_ark_plugin/skills/client-sdk/SKILL.md` (MD032 x2)
- `projectaria_ark_plugin/skills/client-sdk-ros2-integration/SKILL.md` (MD040 x1)
- `projectaria_ark_plugin/skills/cloud-streaming/SKILL.md` (MD040 x3)
- `projectaria_ark_plugin/skills/mps/SKILL.md` (MD032 x1)
- `projectaria_ark_plugin/skills/projectaria-tools/SKILL.md` (MD032 x1)

___

Differential Revision: D109348371

fbshipit-source-id: dae9ad4d107368a62afcee0c82b691a81b754a01

Author: kongchen1992

projectaria_ark_plugin/skills/aria-knowledge/SKILL.md

@@ -9,7 +9,7 @@ This skill is the **knowledge index** for Project Aria Gen 2 and the Aria Resear
 
 ## How to use this skill
 
-```
+```text
 Question type                         → Action
 ─────────────────────────────────────────────────────────────────────────
 What is X? / How does Y work?         → Answer from this skill
@@ -105,7 +105,6 @@ Key behavior:
 
 For channel peak wavelengths, sample rate, the full processing equations (normalize / flux / lux / CCT), factory calibration JSON layout, gain LUT, saturation rate, and PAT loading code: `/technical-specs/device/als`.
 
-
 ### IMU noise model
 
 Aria's stochastic IMU error is modeled as three additive components:
@@ -221,7 +220,7 @@ CPF is the midpoint of the left and right nominal pupil frames. **It exists only
 
 **Recommendation: don't use CPF.** Use a sensor-frame relative pose instead:
 
-```
+```text
 T_sensor1_sensor2 = T_Device_sensor1.inverse() * T_Device_sensor2
 ```
 

projectaria_ark_plugin/skills/client-sdk-ros2-integration/SKILL.md

@@ -45,7 +45,7 @@ Any other package name fails with `ImportError`. The `aria_data_types` package c
 
 ## Workflow
 
-```
+```text
 1. Extract SDK samples       python3 -m aria.extract_sdk_samples --out ~/Downloads
                               → yields AriaRaw.msg, ros2_publisher_example.py,
                                 ros2_subscriber_example.py

projectaria_ark_plugin/skills/client-sdk/SKILL.md

@@ -149,11 +149,13 @@ The pip package includes both. Gen1 uses `aria` CLI and `import aria.sdk`. Gen2
 **When any Client SDK command fails or returns unexpected output, you MUST consult this section and the official troubleshooting page BEFORE attempting your own diagnosis.** This is not optional. Aria failures have Aria-specific root causes (sandbox blocks, cert mismatches, thermal shutdowns, mDNS issues) that generic debugging will misdiagnose.
 
 Anti-patterns:
+
 - ❌ "I think I know what's wrong" — check the table first; your guess wastes the user's time when the documented fix is one row away.
 - ❌ "Let me try a different approach" — the documented fix exists for a reason. Try it before improvising.
 - ❌ "This looks like a generic Python/network error" — it almost certainly has an Aria-specific cause.
 
 **Resources**:
+
 - **First step always**: `aria_doctor` — configures ports and diagnoses connectivity.
 - **Official troubleshooting page**: https://facebookresearch.github.io/projectaria_tools/gen2/ark/support/sdk — covers symptoms not listed below.
 

projectaria_ark_plugin/skills/cloud-streaming/SKILL.md

@@ -21,7 +21,7 @@ If your collection point is on the **same WiFi** as the glasses, plain local str
 
 ## Architecture
 
-```
+```text
 Aria Glasses  ──(WiFi → internet)──►  Your HTTPS Server :6768
                   HTTPS POST              (decode / store / forward)
 ```
@@ -40,7 +40,7 @@ The glasses open an HTTPS connection to a URL you provide and POST sensor data c
 
 The certificates were generated when the SDK was first set up. They live on the PC where the SDK was installed at:
 
-```
+```text
 ~/.aria/streaming-certs/persistent/
 ├── subscriber.pem        # server cert (PEM)
 ├── subscriber-key.pem    # server private key
@@ -103,7 +103,7 @@ Without batching, the device will hit its thermal shutdown threshold (~44 °C) 
 
 **Workaround**: deploy a **public relay** — a small VM with a public IP that the glasses POST to — and forward via SSH / WireGuard tunnel into your internal server:
 
-```
+```text
 Aria Glasses ──► Public Relay (VM, public IP)  ─tunnel─►  Your Internal Server
                   HTTPS POST :6768               SSH /                (behind VPN)
                                                  WireGuard

projectaria_ark_plugin/skills/mps/SKILL.md

@@ -81,6 +81,7 @@ On-device eye gaze and VIO are embedded in the VRS during recording (accessible
 **When any MPS command fails, returns unexpected output, or produces low-quality results, you MUST consult this section and the official troubleshooting page BEFORE attempting your own diagnosis.** This is not optional. MPS failures have MPS-specific root causes (health check rejections, insufficient recording length, coordinate frame mismatches) that generic debugging will misdiagnose.
 
 Anti-patterns:
+
 - ❌ "I think I know what's wrong" — check the list below and the official page first; your guess wastes the user's time when the documented fix is right here.
 - ❌ "Let me try reprocessing" — understand WHY it failed first. Blindly rerunning with `--force` wastes upload time and quota.
 - ❌ "This looks like a generic upload/network error" — MPS has specific retry and resumable upload logic. Check the CLI guide before improvising.

projectaria_ark_plugin/skills/projectaria-tools/SKILL.md

@@ -242,6 +242,7 @@ Source: https://github.com/facebookresearch/projectaria_tools/tree/main/projecta
 Exports **on-device** machine-perception streams (VIO, eye gaze, hand tracking, online calibration) from a Gen 2 VRS into CSV / JSONL files in the **same format as cloud MPS outputs**.
 
 **Use when**:
+
 - You want to compare on-device perception against cloud MPS on the same recording.
 - You want to reuse MPS-loading code on a recording you haven't sent through MPS.