Flatten QUICKSTART commands to single lines for easier copy-paste.

Co-authored-by: Cursor <cursoragent@cursor.com>

QUICKSTART.md

@@ -131,10 +131,7 @@ URL that nodes should use for outbound relay connections:
 .venv/bin/meshnet-relay --host 0.0.0.0 --port 8765
 
 # Terminal 2 — tracker
-.venv/bin/meshnet-tracker start \
+.venv/bin/meshnet-tracker start --host 0.0.0.0 --port 8081 --relay-url wss://ai.neuron.d-popov.com/ws
-  --host 0.0.0.0 \
-  --port 8081 \
-  --relay-url wss://ai.neuron.d-popov.com/ws
 ```
 
 If this host sits behind Nginx Proxy Manager, point `/` and `/v1/*` at tracker
@@ -249,9 +246,7 @@ meshnet-node start --tracker https://ai.neuron.d-popov.com --model Qwen/Qwen2.5-
 If the wrong entry point is shadowing, invoke via the full conda path:
 
 ```powershell
-C:\Users\popov\miniforge3\Scripts\meshnet-node.exe start `
+C:\Users\popov\miniforge3\Scripts\meshnet-node.exe start --tracker https://ai.neuron.d-popov.com --model Qwen/Qwen2.5-0.5B-Instruct
-  --tracker https://ai.neuron.d-popov.com `
-  --model Qwen/Qwen2.5-0.5B-Instruct
 ```
 
 #### Option B — isolated virtualenv (fresh machine, no existing torch)
@@ -297,12 +292,7 @@ Use the IPv4 address on the active Ethernet/Wi-Fi adapter, for example
 Administrator once:
 
 ```powershell
-New-NetFirewallRule `
+New-NetFirewallRule -DisplayName "Meshnet node 8005" -Direction Inbound -Action Allow -Protocol TCP -LocalPort 8005
-  -DisplayName "Meshnet node 8005" `
-  -Direction Inbound `
-  -Action Allow `
-  -Protocol TCP `
-  -LocalPort 8005
 ```
 
 5. Start the Windows node from normal PowerShell. Replace the tracker and
@@ -310,18 +300,10 @@ advertised host values with your actual LAN addresses:
 
 ```powershell
 $env:HF_HOME = "D:\DEV\models"
-
+.\.venv\Scripts\meshnet-node.exe start --tracker http://192.168.0.179:8081 --model Qwen/Qwen2.5-0.5B-Instruct --shard-start 12 --shard-end 23 --quantization bfloat16 --host 0.0.0.0 --advertise-host 192.168.0.42 --port 8005
-.\.venv\Scripts\meshnet-node.exe start `
-  --tracker http://192.168.0.179:8081 `
-  --model Qwen/Qwen2.5-0.5B-Instruct `
-  --shard-start 12 --shard-end 23 `
-  --quantization bfloat16 `
-  --host 0.0.0.0 `
-  --advertise-host 192.168.0.42 `
-  --port 8005
 ```
 
-One-line variants (direct LAN — node must be reachable by IP from other machines):
+Other start examples (direct LAN — node must be reachable by IP from other machines):
 
 ```powershell
 .\.venv\Scripts\meshnet-node.exe start --tracker http://192.168.0.179:8081 --model Qwen/Qwen2.5-0.5B-Instruct --advertise-host 192.168.0.20
@@ -466,10 +448,7 @@ After NPM is correct, start relay and tracker on the LAN machine:
 .venv/bin/meshnet-relay --host 0.0.0.0 --port 8765
 
 # Terminal 2 — tracker (advertises relay to nodes)
-.venv/bin/meshnet-tracker start \
+.venv/bin/meshnet-tracker start --host 0.0.0.0 --port 8081 --relay-url wss://ai.neuron.d-popov.com/ws
-  --host 0.0.0.0 \
-  --port 8081 \
-  --relay-url wss://ai.neuron.d-popov.com/ws
 ```
 
 Nodes using `https://ai.neuron.d-popov.com` should then log:
@@ -491,9 +470,7 @@ opens a persistent outbound WebSocket. If the relay connection drops, the node
 keeps retrying it.
 
 ```bash
-.venv/bin/meshnet-node start \
+.venv/bin/meshnet-node start --tracker https://ai.neuron.d-popov.com --model Qwen/Qwen2.5-0.5B-Instruct
-  --tracker https://ai.neuron.d-popov.com \
-  --model Qwen/Qwen2.5-0.5B-Instruct
 ```
 
 No authentication is required in the prototype. The first public node for a model
@@ -555,16 +532,10 @@ In WSL2 (which gets a `172.x.x.x` virtual IP — unreachable from other machines
 
 ```bash
 # WSL2 Terminal 1 — head node (layers 0–11, handles chat requests)
-.venv/bin/meshnet-node start \
+.venv/bin/meshnet-node start --tracker https://ai.neuron.d-popov.com --model Qwen/Qwen2.5-0.5B-Instruct --shard-start 0 --shard-end 11
-  --tracker https://ai.neuron.d-popov.com \
-  --model Qwen/Qwen2.5-0.5B-Instruct \
-  --shard-start 0 --shard-end 11
 
 # WSL2 Terminal 2 — tail node (layers 12–23)
-.venv/bin/meshnet-node start \
+.venv/bin/meshnet-node start --tracker https://ai.neuron.d-popov.com --model Qwen/Qwen2.5-0.5B-Instruct --shard-start 12 --shard-end 23
-  --tracker https://ai.neuron.d-popov.com \
-  --model Qwen/Qwen2.5-0.5B-Instruct \
-  --shard-start 12 --shard-end 23
 ```
 
 Both nodes connect to the relay automatically. When a chat request arrives at Node A,
@@ -573,14 +544,7 @@ it forwards activations to Node B via `wss://ai.neuron.d-popov.com/rpc/{peer_id_
 Send inference through the tracker (which picks the head node and injects the route):
 
 ```bash
-curl -s https://ai.neuron.d-popov.com/v1/chat/completions \
+curl -s https://ai.neuron.d-popov.com/v1/chat/completions -H "Content-Type: application/json" -H "Authorization: Bearer sk-mesh-<your-key>" -d '{"model": "Qwen/Qwen2.5-0.5B-Instruct", "messages": [{"role": "user", "content": "What is 7 times 8?"}], "stream": false}' | python3 -m json.tool
-  -H "Content-Type: application/json" \
-  -H "Authorization: Bearer sk-mesh-<your-key>" \
-  -d '{
-    "model": "Qwen/Qwen2.5-0.5B-Instruct",
-    "messages": [{"role": "user", "content": "What is 7 times 8?"}],
-    "stream": false
-  }' | python3 -m json.tool
 ```
 
 Or send directly to Node A's local port (within WSL):
@@ -608,24 +572,18 @@ refill during testing.
 
 ```bash
 # 1. Register (once)
-curl -s https://<tracker>/v1/auth/register \
+curl -s https://<tracker>/v1/auth/register -H "Content-Type: application/json" -d '{"email": "you@example.com", "password": "hunter22-or-better"}'
-  -H "Content-Type: application/json" \
-  -d '{"email": "you@example.com", "password": "hunter22-or-better"}'
 # → {"session_token": "...", ...}
 
 # 2. Create an API key (session token from step 1)
-curl -s https://<tracker>/v1/account/keys -X POST \
+curl -s https://<tracker>/v1/account/keys -X POST -H "Authorization: Bearer <session_token>"
-  -H "Authorization: Bearer <session_token>"
 # → {"api_key": "sk-mesh-...", "caller_credit_granted": true}
 
 # 3. Check balance / usage
 curl -s https://<tracker>/v1/account -H "Authorization: Bearer <session_token>"
 
 # 4. (devnet trackers only) top up a key
-curl -s https://<tracker>/v1/account/topup -X POST \
+curl -s https://<tracker>/v1/account/topup -X POST -H "Authorization: Bearer <session_token>" -H "Content-Type: application/json" -d '{"api_key": "sk-mesh-..."}'
-  -H "Authorization: Bearer <session_token>" \
-  -H "Content-Type: application/json" \
-  -d '{"api_key": "sk-mesh-..."}'
 ```
 
 Operator side: both features default to 1 USDT (`--starting-credit` /
@@ -661,12 +619,7 @@ Keep this terminal open.
 
 ```bash
 cd /run/media/popov/d/DEV/repos/d-popov.com/AI
-HF_HOME=/run/media/popov/d/DEV/models \
+HF_HOME=/run/media/popov/d/DEV/models .venv/bin/meshnet-node start --model Qwen/Qwen2.5-0.5B-Instruct --quantization bfloat16 --tracker http://localhost:8080 --port 8001
-.venv/bin/meshnet-node start \
-  --model Qwen/Qwen2.5-0.5B-Instruct \
-  --quantization bfloat16 \
-  --tracker http://localhost:8080 \
-  --port 8001
 ```
 
 Shard range is **auto-detected** from the curated catalog (no network call for known
@@ -708,13 +661,7 @@ If you started the node with `--port 8001`, send the request directly to that
 head node:
 
 ```bash Qwen2.5-0.5B-Instruct
-curl -s http://localhost:8001/v1/chat/completions \
+curl -s http://localhost:8001/v1/chat/completions -H "Content-Type: application/json" -d '{"model": "qwen2.5-0.5b", "messages": [{"role": "user", "content": "What is 7 times 8? Answer in one word."}], "stream": false}' | python3 -m json.tool
-  -H "Content-Type: application/json" \
-  -d '{
-    "model": "qwen2.5-0.5b",
-    "messages": [{"role": "user", "content": "What is 7 times 8? Answer in one word."}],
-    "stream": false
-  }' | python3 -m json.tool
 ```
 
 If you did not pass `--port`, `meshnet-node start` uses the first free port at
@@ -724,21 +671,13 @@ To test tracker routing/proxying, send the same OpenAI-compatible request to the
 tracker, using either the full HuggingFace repo or the quick alias:
 
 ```bash
-curl -s http://localhost:8080/v1/chat/completions \
+curl -s http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{"model": "qwen2.5-0.5b", "messages": [{"role": "user", "content": "What is 7 times 8? Answer in one word."}], "stream": false}' | python3 -m json.tool
-  -H "Content-Type: application/json" \
-  -d '{
-    "model": "qwen2.5-0.5b",
-    "messages": [{"role": "user", "content": "What is 7 times 8? Answer in one word."}],
-    "stream": false
-  }' | python3 -m json.tool
 ```
 
 Or use the test script:
 
 ```bash
-.venv/bin/python scripts/test_lan_inference.py \
+.venv/bin/python scripts/test_lan_inference.py --tracker http://localhost:8080 --gateway http://localhost:8001
-  --tracker http://localhost:8080 \
-  --gateway http://localhost:8001
 ```
 
 ---
@@ -749,24 +688,12 @@ Split Qwen2.5-0.5B's 24 layers across two node processes to test the sharded pip
 
 **Node A — layers 0–11 (tracker mode, serves chat completions):**
 ```bash
-HF_HOME=/run/media/popov/d/DEV/models \
+HF_HOME=/run/media/popov/d/DEV/models .venv/bin/meshnet-node start --model Qwen/Qwen2.5-0.5B-Instruct --shard-start 0 --shard-end 11 --quantization bfloat16 --tracker http://localhost:8080 --port 8001
-.venv/bin/meshnet-node start \
-  --model Qwen/Qwen2.5-0.5B-Instruct \
-  --shard-start 0 --shard-end 11 \
-  --quantization bfloat16 \
-  --tracker http://localhost:8080 \
-  --port 8001
 ```
 
 **Node B — layers 12–23:**
 ```bash
-HF_HOME=/run/media/popov/d/DEV/models \
+HF_HOME=/run/media/popov/d/DEV/models .venv/bin/meshnet-node start --model Qwen/Qwen2.5-0.5B-Instruct --shard-start 12 --shard-end 23 --quantization bfloat16 --tracker http://localhost:8080 --port 8002
-.venv/bin/meshnet-node start \
-  --model Qwen/Qwen2.5-0.5B-Instruct \
-  --shard-start 12 --shard-end 23 \
-  --quantization bfloat16 \
-  --tracker http://localhost:8080 \
-  --port 8002
 ```
 
 Send the request to Node A — it tokenizes, runs layers 0–11, passes binary