feat: integrate Trackio for experiment tracking, add GRPO training support, and deploy web-based monitoring tools

.agents/skills/openenv-cli/SKILL.md

@@ -0,0 +1,18 @@
+---
+name: openenv-cli
+description: "OpenEnv CLI (`openenv`) for scaffolding, validating, building, and pushing OpenEnv environments."
+---
+
+Install: `pip install openenv-core`
+
+The OpenEnv CLI command `openenv` is available.
+Use `openenv --help` to view available commands.
+
+Generated with `openenv-core v0.2.3`. Run `openenv skills add --force` to regenerate.
+
+## Tips
+
+- Start with `openenv init <env_name>` to scaffold a new environment
+- Validate projects with `openenv validate`
+- Build and deploy with `openenv build` and `openenv push`
+- Use `openenv <command> --help` for command-specific options

.agents/skills/trackio/SKILL.md

@@ -0,0 +1,124 @@
+---
+name: hugging-face-trackio
+description: Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.
+---
+
+# Trackio - Experiment Tracking for ML Training
+
+Trackio is an experiment tracking library for logging and visualizing ML training metrics. It syncs to Hugging Face Spaces for real-time monitoring dashboards.
+
+## Three Interfaces
+
+| Task | Interface | Reference |
+|------|-----------|-----------|
+| **Logging metrics** during training | Python API | [logging_metrics.md](logging_metrics.md) |
+| **Firing alerts** for training diagnostics | Python API | [alerts.md](alerts.md) |
+| **Retrieving metrics & alerts** after/during training | CLI | [retrieving_metrics.md](retrieving_metrics.md) |
+| **Inspecting storage schema and running direct SQL** | CLI | [storage_schema.md](storage_schema.md) |
+
+## When to Use Each
+
+### Python API → Logging
+
+Use `import trackio` in your training scripts to log metrics:
+
+- Initialize tracking with `trackio.init()`
+- Log metrics with `trackio.log()` or use TRL's `report_to="trackio"`
+- Finalize with `trackio.finish()`
+
+**Key concept**: For remote/cloud training, pass `space_id` — metrics sync to a Space dashboard so they persist after the instance terminates.
+
+→ See [logging_metrics.md](logging_metrics.md) for setup, TRL integration, and configuration options.
+
+### Python API → Alerts
+
+Insert `trackio.alert()` calls in training code to flag important events — like inserting print statements for debugging, but structured and queryable:
+
+- `trackio.alert(title="...", level=trackio.AlertLevel.WARN)` — fire an alert
+- Three severity levels: `INFO`, `WARN`, `ERROR`
+- Alerts are printed to terminal, stored in the database, shown in the dashboard, and optionally sent to webhooks (Slack/Discord)
+
+**Key concept for LLM agents**: Alerts are the primary mechanism for autonomous experiment iteration. An agent should insert alerts into training code for diagnostic conditions (loss spikes, NaN gradients, low accuracy, training stalls). Since alerts are printed to the terminal, an agent that is watching the training script's output will see them automatically. For background or detached runs, the agent can poll via CLI instead.
+
+→ See [alerts.md](alerts.md) for the full alerts API, webhook setup, and autonomous agent workflows.
+
+### CLI → Retrieving
+
+Use the `trackio` command to query logged metrics and alerts:
+
+- `trackio list projects/runs/metrics` — discover what's available
+- `trackio get project/run/metric` — retrieve summaries and values
+- `trackio query project --project <name> --sql "SELECT ..."` — run catch-all read-only SQL
+- `trackio list alerts --project <name> --json` — retrieve alerts
+- `trackio show` — launch the dashboard
+- `trackio sync` — sync to HF Space
+
+**Key concept**: Add `--json` for programmatic output suitable for automation and LLM agents.
+
+**Remote Spaces**: Add `--space <space_id_or_url>` to any `list`/`get`/`query` command to query a remote HF Space instead of local data. Use `--hf-token` for private Spaces.
+
+→ See [retrieving_metrics.md](retrieving_metrics.md) for all commands, workflows, and JSON output formats.
+→ See [storage_schema.md](storage_schema.md) for SQLite tables, parquet layout, and direct query examples.
+
+## Minimal Logging Setup
+
+```python
+import trackio
+
+trackio.init(project="my-project", space_id="username/trackio")
+trackio.log({"loss": 0.1, "accuracy": 0.9})
+trackio.log({"loss": 0.09, "accuracy": 0.91})
+trackio.finish()
+```
+
+### Minimal Retrieval
+
+```bash
+trackio list projects --json
+trackio get metric --project my-project --run my-run --metric loss --json
+trackio query project --project my-project --sql "SELECT name FROM sqlite_master WHERE type = 'table'" --json
+
+# Query a remote Space
+trackio list projects --space username/my-space --json
+```
+
+## Autonomous ML Experiment Workflow
+
+When running experiments autonomously as an LLM agent, the recommended workflow is:
+
+1. **Set up training with alerts** — insert `trackio.alert()` calls for diagnostic conditions
+2. **Launch training** — run the script in the background
+3. **Poll for alerts** — use `trackio list alerts --project <name> --json --since <timestamp>` to check for new alerts
+4. **Read metrics** — use `trackio get metric ...` to inspect specific values
+5. **Iterate** — based on alerts and metrics, stop the run, adjust hyperparameters, and launch a new run
+
+```python
+import trackio
+
+trackio.init(project="my-project", config={"lr": 1e-4})
+
+for step in range(num_steps):
+    loss = train_step()
+    trackio.log({"loss": loss, "step": step})
+
+    if step > 100 and loss > 5.0:
+        trackio.alert(
+            title="Loss divergence",
+            text=f"Loss {loss:.4f} still high after {step} steps",
+            level=trackio.AlertLevel.ERROR,
+        )
+    if step > 0 and abs(loss) < 1e-8:
+        trackio.alert(
+            title="Vanishing loss",
+            text="Loss near zero — possible gradient collapse",
+            level=trackio.AlertLevel.WARN,
+        )
+
+trackio.finish()
+```
+
+Then poll from a separate terminal/process:
+
+```bash
+trackio list alerts --project my-project --json --since "2025-01-01T00:00:00"
+```

.agents/skills/trackio/alerts.md

@@ -0,0 +1,199 @@
+# Trackio Alerts
+
+Alerts let you flag important training events directly from code. They are the primary mechanism for LLM agents to diagnose runs and iterate autonomously on ML experiments.
+
+Alerts are printed to the terminal, stored in the database, displayed in the dashboard, and optionally sent to webhooks (Slack/Discord).
+
+<img width="2972" height="1694" alt="image" src="https://github.com/user-attachments/assets/02d938f8-51a9-4706-85c4-d95b7645bcf4" />
+
+
+## Core API
+
+### trackio.alert()
+
+```python
+trackio.alert(
+    title="Loss divergence",                    # Short title (required)
+    text="Loss 5.2 still high after 200 steps", # Detailed description (optional)
+    level=trackio.AlertLevel.WARN,               # INFO, WARN, or ERROR (default: WARN)
+    webhook_url="https://hooks.slack.com/...",   # Per-alert webhook override (optional)
+)
+```
+
+### Alert Levels
+
+| Level | Usage |
+|-------|-------|
+| `trackio.AlertLevel.INFO` | Informational milestones (checkpoints saved, eval completed) |
+| `trackio.AlertLevel.WARN` | Potential issues (loss plateau, low accuracy, high gradient norm) |
+| `trackio.AlertLevel.ERROR` | Critical failures (NaN loss, divergence, OOM) |
+
+### Webhook Support
+
+Set a global webhook URL via `trackio.init()` or the `TRACKIO_WEBHOOK_URL` environment variable. Alerts are auto-formatted for Slack and Discord URLs.
+
+```python
+trackio.init(
+    project="my-project",
+    webhook_url="https://hooks.slack.com/services/...",
+    webhook_min_level=trackio.AlertLevel.WARN,  # Only send WARN+ to webhook
+)
+```
+
+Per-alert override:
+
+```python
+trackio.alert(
+    title="Critical failure",
+    level=trackio.AlertLevel.ERROR,
+    webhook_url="https://hooks.slack.com/services/...",  # Overrides global URL
+)
+```
+
+Environment variables:
+- `TRACKIO_WEBHOOK_URL` — global webhook URL
+- `TRACKIO_WEBHOOK_MIN_LEVEL` — minimum level for webhook delivery (`info`, `warn`, `error`)
+
+## Retrieving Alerts (CLI)
+
+```bash
+# List all alerts for a project
+trackio list alerts --project my-project --json
+
+# Filter by run or level
+trackio list alerts --project my-project --run my-run --level error --json
+
+# Poll for new alerts since a timestamp (efficient for agents)
+trackio list alerts --project my-project --json --since "2025-06-01T12:00:00"
+```
+
+### JSON Output Structure
+
+```json
+{
+  "project": "my-project",
+  "run": null,
+  "level": null,
+  "since": "2025-06-01T12:00:00",
+  "alerts": [
+    {
+      "run": "run-name",
+      "title": "Loss divergence",
+      "text": "Loss 5.2 still high after 200 steps",
+      "level": "warn",
+      "step": 200,
+      "timestamp": "2025-06-01T12:05:30"
+    }
+  ]
+}
+```
+
+## Autonomous Agent Workflow
+
+The recommended pattern for an LLM agent running ML experiments:
+
+### 1. Insert Alerts Into Training Code
+
+Add diagnostic `trackio.alert()` calls for conditions the agent should react to:
+
+```python
+import trackio
+
+trackio.init(project="hyperparam-sweep", config={"lr": lr, "batch_size": bs})
+
+for step in range(num_steps):
+    loss = train_step()
+    trackio.log({"loss": loss, "step": step})
+
+    if step > 200 and loss > 5.0:
+        trackio.alert(
+            title="Loss divergence",
+            text=f"Loss {loss:.4f} still above 5.0 after {step} steps — learning rate may be too high",
+            level=trackio.AlertLevel.ERROR,
+        )
+
+    if step > 500 and loss_delta < 0.001:
+        trackio.alert(
+            title="Training stall",
+            text=f"Loss barely changed over last 100 steps (delta={loss_delta:.6f})",
+            level=trackio.AlertLevel.WARN,
+        )
+
+    if math.isnan(loss):
+        trackio.alert(
+            title="NaN loss",
+            text="Loss became NaN — training is broken",
+            level=trackio.AlertLevel.ERROR,
+        )
+        break
+
+trackio.finish()
+```
+
+### 2. Monitor Alerts
+
+Alerts are automatically printed to the terminal when fired. If the agent is watching the training script's output (e.g. running in the foreground or tailing logs), it will see alerts immediately — no polling needed.
+
+For background or detached runs, poll for alerts via CLI:
+
+```bash
+# Poll for alerts (run periodically)
+trackio list alerts --project hyperparam-sweep --json --since "2025-06-01T00:00:00"
+```
+
+### 3. Inspect Metrics Around the Alert
+
+When an alert fires, use `trackio get snapshot` to see all metrics at that point:
+
+```bash
+# Alert fired at step 200 — get all metrics in a ±5 step window
+trackio get snapshot --project hyperparam-sweep --run run-1 --around 200 --window 5 --json
+
+# Or inspect a single metric around the alert's timestamp
+trackio get metric --project hyperparam-sweep --run run-1 --metric loss --around 200 --window 10 --json
+```
+
+### 4. React and Iterate
+
+Based on alerts:
+- **ERROR alerts** → stop the run, adjust hyperparameters, relaunch
+- **WARN alerts** → inspect metrics with `trackio get snapshot ...`, decide whether to intervene
+- **INFO alerts** → note progress, continue monitoring
+
+### 5. Compare Across Runs
+
+```bash
+# Check metrics from previous runs
+trackio get run --project hyperparam-sweep --run run-1 --json
+trackio get metric --project hyperparam-sweep --run run-1 --metric loss --json
+
+# Launch new run with adjusted config
+python train.py --lr 5e-5
+```
+
+## Using Alerts with Transformers / TRL
+
+When using `report_to="trackio"`, you don't control the training loop directly. Use a `TrainerCallback` to fire alerts:
+
+```python
+from transformers import TrainerCallback
+
+class AlertCallback(TrainerCallback):
+    def on_log(self, args, state, control, logs=None, **kwargs):
+        if "trackio" not in args.report_to:
+            return
+        if logs and "loss" in logs:
+            if logs["loss"] > 5.0 and state.global_step > 100:
+                trackio.alert(
+                    title="High loss",
+                    text=f"Loss {logs['loss']:.4f} at step {state.global_step}",
+                    level=trackio.AlertLevel.ERROR,
+                )
+
+trainer = SFTTrainer(
+    model=model,
+    args=SFTConfig(output_dir="./out", report_to="trackio"),
+    callbacks=[AlertCallback()],
+    ...
+)
+```

.agents/skills/trackio/logging_metrics.md

@@ -0,0 +1,206 @@
+# Logging Metrics with Trackio
+
+**Trackio** is a lightweight, free experiment tracking library from Hugging Face. It provides a wandb-compatible API for logging metrics with local-first design.
+
+- **GitHub**: [gradio-app/trackio](https://github.com/gradio-app/trackio)
+- **Docs**: [huggingface.co/docs/trackio](https://huggingface.co/docs/trackio/index)
+
+## Installation
+
+```bash
+pip install trackio
+# or
+uv pip install trackio
+```
+
+## Core API
+
+### Basic Usage
+
+```python
+import trackio
+
+# Initialize a run
+trackio.init(
+    project="my-project",
+    config={"learning_rate": 0.001, "epochs": 10}
+)
+
+# Log metrics during training
+for epoch in range(10):
+    loss = train_epoch()
+    trackio.log({"loss": loss, "epoch": epoch})
+
+# Finalize the run
+trackio.finish()
+```
+
+### Key Functions
+
+| Function | Purpose |
+|----------|---------|
+| `trackio.init(...)` | Start a new tracking run |
+| `trackio.log(dict)` | Log metrics (called repeatedly during training) |
+| `trackio.finish()` | Finalize run and ensure all metrics are saved |
+| `trackio.show()` | Launch the local dashboard |
+| `trackio.sync(...)` | Sync local project to HF Space |
+
+## trackio.init() Parameters
+
+```python
+trackio.init(
+    project="my-project",           # Project name (groups runs together)
+    name="run-name",                # Optional: name for this specific run
+    config={...},                   # Hyperparameters and config to log
+    space_id="username/trackio",    # Optional: sync to HF Space for remote dashboard
+    group="experiment-group",       # Optional: group related runs
+)
+```
+
+## Local vs Remote Dashboard
+
+### Local (Default)
+
+By default, trackio stores metrics in a local SQLite database and runs the dashboard locally:
+
+```python
+trackio.init(project="my-project")
+# ... training ...
+trackio.finish()
+
+# Launch local dashboard
+trackio.show()
+```
+
+Or from terminal:
+```bash
+trackio show --project my-project
+```
+
+### Remote (HF Space)
+
+Pass `space_id` to sync metrics to a Hugging Face Space for persistent, shareable dashboards:
+
+```python
+trackio.init(
+    project="my-project",
+    space_id="username/trackio"  # Auto-creates Space if it doesn't exist
+)
+```
+
+⚠️ **For remote training** (cloud GPUs, HF Jobs, etc.): Always use `space_id` since local storage is lost when the instance terminates.
+
+### Sync Local to Remote
+
+Sync existing local projects to a Space:
+
+```python
+trackio.sync(project="my-project", space_id="username/my-experiments")
+```
+
+## wandb Compatibility
+
+Trackio is API-compatible with wandb. Drop-in replacement:
+
+```python
+import trackio as wandb
+
+wandb.init(project="my-project")
+wandb.log({"loss": 0.5})
+wandb.finish()
+```
+
+## TRL Integration
+
+When using TRL trainers, set `report_to="trackio"` for automatic metric logging:
+
+```python
+from trl import SFTConfig, SFTTrainer
+import trackio
+
+trackio.init(
+    project="sft-training",
+    space_id="username/trackio",
+    config={"model": "Qwen/Qwen2.5-0.5B", "dataset": "trl-lib/Capybara"}
+)
+
+config = SFTConfig(
+    output_dir="./output",
+    report_to="trackio",  # Automatic metric logging
+    # ... other config
+)
+
+trainer = SFTTrainer(model=model, args=config, ...)
+trainer.train()
+trackio.finish()
+```
+
+## What Gets Logged
+
+With TRL/Transformers integration, trackio automatically captures:
+- Training loss
+- Learning rate
+- Eval metrics
+- Training throughput
+
+For manual logging, log any numeric metrics:
+
+```python
+trackio.log({
+    "train_loss": 0.5,
+    "train_accuracy": 0.85,
+    "val_loss": 0.4,
+    "val_accuracy": 0.88,
+    "epoch": 1
+})
+```
+
+## Grouping Runs
+
+Use `group` to organize related experiments in the dashboard sidebar:
+
+```python
+# Group by experiment type
+trackio.init(project="my-project", name="baseline-v1", group="baseline")
+trackio.init(project="my-project", name="augmented-v1", group="augmented")
+
+# Group by hyperparameter
+trackio.init(project="hyperparam-sweep", name="lr-0.001", group="lr_0.001")
+trackio.init(project="hyperparam-sweep", name="lr-0.01", group="lr_0.01")
+```
+
+## Configuration Best Practices
+
+Keep config minimal — only log what's useful for comparing runs:
+
+```python
+trackio.init(
+    project="qwen-sft-capybara",
+    name="baseline-lr2e5",
+    config={
+        "model": "Qwen/Qwen2.5-0.5B",
+        "dataset": "trl-lib/Capybara",
+        "learning_rate": 2e-5,
+        "num_epochs": 3,
+        "batch_size": 8,
+    }
+)
+```
+
+## Embedding Dashboards
+
+Embed Space dashboards in websites with query parameters:
+
+```html
+<iframe 
+  src="https://username-trackio.hf.space/?project=my-project&metrics=train_loss,val_loss&sidebar=hidden" 
+  style="width:1600px; height:500px; border:0;">
+</iframe>
+```
+
+Query parameters:
+- `project`: Filter to specific project
+- `metrics`: Comma-separated metric names to show
+- `sidebar`: `hidden` or `collapsed`
+- `smoothing`: 0-20 (smoothing slider value)
+- `xmin`, `xmax`: X-axis limits

.agents/skills/trackio/retrieving_metrics.md

@@ -0,0 +1,298 @@
+# Retrieving Metrics with Trackio CLI
+
+The `trackio` CLI provides direct terminal access to query Trackio experiment tracking data without needing to start the MCP server. Commands work against local data by default, or against a remote HF Space when `--space` is provided.
+
+## Quick Command Reference
+
+| Task | Command |
+|------|---------|
+| List projects | `trackio list projects` |
+| List runs | `trackio list runs --project <name>` |
+| List metrics | `trackio list metrics --project <name> --run <name>` |
+| List system metrics | `trackio list system-metrics --project <name> --run <name>` |
+| List alerts | `trackio list alerts --project <name> [--run <name>] [--level <level>] [--since <timestamp>]` |
+| Get project summary | `trackio get project --project <name>` |
+| Get run summary | `trackio get run --project <name> --run <name>` |
+| Get metric values | `trackio get metric --project <name> --run <name> --metric <name>` |
+| Get metric at step | `trackio get metric ... --metric <name> --step <N>` |
+| Get metric around step | `trackio get metric ... --metric <name> --around <N> --window <W>` |
+| Get all metrics snapshot | `trackio get snapshot --project <name> --run <name> --step <N>` |
+| Get system metrics | `trackio get system-metric --project <name> --run <name>` |
+| Run direct SQL | `trackio query project --project <name> --sql "SELECT ..."` |
+| Query remote Space | `trackio list projects --space <space_id_or_url>` |
+| Show dashboard | `trackio show [--project <name>]` |
+| Sync to Space | `trackio sync --project <name> --space-id <space_id>` |
+
+## Core Commands
+
+### List Commands
+
+```bash
+trackio list projects                                    # List all projects
+trackio list projects --json                            # JSON output
+
+trackio list runs --project <name>                      # List runs in project
+trackio list runs --project <name> --json               # JSON output
+
+trackio list metrics --project <name> --run <name>      # List metrics for run
+trackio list metrics --project <name> --run <name> --json
+
+trackio list system-metrics --project <name> --run <name>  # List system metrics
+trackio list system-metrics --project <name> --run <name> --json
+
+trackio list alerts --project <name>                       # List alerts
+trackio list alerts --project <name> --run <name> --json   # Filter by run
+trackio list alerts --project <name> --level error --json  # Filter by level
+trackio list alerts --project <name> --json --since <ts>   # Poll since timestamp
+```
+
+### Get Commands
+
+```bash
+trackio get project --project <name>                    # Project summary
+trackio get project --project <name> --json             # JSON output
+
+trackio get run --project <name> --run <name>           # Run summary
+trackio get run --project <name> --run <name> --json
+
+trackio get metric --project <name> --run <name> --metric <name>  # Metric values
+trackio get metric --project <name> --run <name> --metric <name> --json
+trackio get metric ... --metric <name> --step 200                 # At exact step
+trackio get metric ... --metric <name> --around 200 --window 10   # ±10 steps
+trackio get metric ... --metric <name> --at-time <ts> --window 60 # ±60 seconds
+
+trackio get snapshot --project <name> --run <name> --step 200 --json       # All metrics at step
+trackio get snapshot --project <name> --run <name> --around 200 --window 5 --json  # Window
+trackio get snapshot --project <name> --run <name> --at-time <ts> --window 60 --json
+
+trackio get system-metric --project <name> --run <name>           # All system metrics
+trackio get system-metric --project <name> --run <name> --metric <name>  # Specific metric
+trackio get system-metric --project <name> --run <name> --json
+```
+
+### Query Command
+
+```bash
+trackio query project --project <name> --sql "SELECT name FROM sqlite_master WHERE type = 'table'"
+trackio query project --project <name> --sql "PRAGMA table_info(metrics)" --json
+trackio query project --project <name> --sql "SELECT run_name, MAX(step) AS last_step FROM metrics GROUP BY run_name"
+```
+
+### Remote Space Queries
+
+All `list`, `get`, and `query` commands support querying a remote HF Space with `--space`:
+
+```bash
+trackio list projects --space user/my-space              # Space ID
+trackio list projects --space https://user-my-space.hf.space  # Space URL
+trackio get metric --project <name> --run <name> --metric loss --space user/my-space
+trackio query project --project <name> --sql "SELECT COUNT(*) AS num_alerts FROM alerts" --space user/my-space
+trackio list projects --space user/private-space --hf-token hf_xxx  # Private Space
+```
+
+### Dashboard Commands
+
+```bash
+trackio show                                              # Launch dashboard
+trackio show --project <name>                           # Load specific project
+trackio show --theme <theme>                            # Custom theme
+trackio show --mcp-server                                # Enable MCP server
+trackio show --color-palette "#FF0000,#00FF00"         # Custom colors
+```
+
+### Sync Commands
+
+```bash
+trackio sync --project <name> --space-id <space_id>     # Sync to HF Space
+trackio sync --project <name> --space-id <space_id> --private  # Private space
+trackio sync --project <name> --space-id <space_id> --force   # Overwrite
+```
+
+## Output Formats
+
+All `list`, `get`, and `query` commands support two output formats:
+
+- **Human-readable** (default): Formatted text for terminal viewing
+- **JSON** (with `--json` flag): Structured JSON for programmatic use
+
+## Common Patterns
+
+### Discover Projects and Runs
+
+```bash
+# List all available projects
+trackio list projects
+
+# List runs in a project
+trackio list runs --project my-project
+
+# Get project overview
+trackio get project --project my-project --json
+```
+
+### Inspect Run Details
+
+```bash
+# Get run summary with all metrics
+trackio get run --project my-project --run my-run --json
+
+# List available metrics
+trackio list metrics --project my-project --run my-run
+
+# Get specific metric values
+trackio get metric --project my-project --run my-run --metric loss --json
+```
+
+### Query System Metrics
+
+```bash
+# List system metrics (GPU, etc.)
+trackio list system-metrics --project my-project --run my-run
+
+# Get all system metric data
+trackio get system-metric --project my-project --run my-run --json
+
+# Get specific system metric
+trackio get system-metric --project my-project --run my-run --metric gpu_utilization --json
+```
+
+### Automation Scripts
+
+```bash
+# Extract latest metric value
+LATEST_LOSS=$(trackio get metric --project my-project --run my-run --metric loss --json | jq -r '.values[-1].value')
+
+# Export run summary to file
+trackio get run --project my-project --run my-run --json > run_summary.json
+
+# Filter runs with jq
+trackio list runs --project my-project --json | jq '.runs[] | select(startswith("train"))'
+
+# Run a direct SQL aggregate
+trackio query project --project my-project --sql "SELECT run_name, MAX(step) AS last_step FROM metrics GROUP BY run_name" --json
+```
+
+### LLM Agent Workflow
+
+```bash
+# 1. Discover available projects
+trackio list projects --json
+
+# 2. Explore project structure
+trackio get project --project my-project --json
+
+# 3. Inspect specific run
+trackio get run --project my-project --run my-run --json
+
+# 4. Query metric values
+trackio get metric --project my-project --run my-run --metric accuracy --json
+
+# 5. Poll for alerts (use --since for efficient incremental polling)
+trackio list alerts --project my-project --json --since "2025-06-01T00:00:00"
+
+# 6. When an alert fires at step N, get all metrics around that point
+trackio get snapshot --project my-project --run my-run --around 200 --window 5 --json
+
+# 7. Fall back to direct SQL for one-off inspection
+trackio query project --project my-project --sql "SELECT timestamp, run_name, level, title FROM alerts ORDER BY timestamp DESC LIMIT 20" --json
+```
+
+## Error Handling
+
+Commands validate inputs and return clear errors:
+
+- Missing project: `Error: Project '<name>' not found.`
+- Missing run: `Error: Run '<name>' not found in project '<project>'.`
+- Missing metric: `Error: Metric '<name>' not found in run '<run>' of project '<project>'.`
+
+All errors exit with non-zero status code and write to stderr.
+
+## Key Options
+
+- `--project`: Project name (required for most commands)
+- `--run`: Run name (required for run-specific commands)
+- `--metric`: Metric name (required for metric-specific commands)
+- `--sql`: Read-only SQL query (for `trackio query`)
+- `--json`: Output in JSON format instead of human-readable
+- `--space`: HF Space ID (e.g. `user/space`) or Space URL to query remotely (for `list`/`get`/`query` commands)
+- `--hf-token`: HF token for accessing private Spaces (for `list`/`get`/`query` commands with `--space`)
+- `--step`: Exact step filter (for `get metric`, `get snapshot`)
+- `--around`: Center step for window filter (for `get metric`, `get snapshot`)
+- `--at-time`: Center ISO timestamp for window filter (for `get metric`, `get snapshot`)
+- `--window`: Window size: ±steps for `--around`, ±seconds for `--at-time` (default: 10)
+- `--level`: Alert level filter (`info`, `warn`, `error`) (for `list alerts`)
+- `--since`: ISO timestamp to filter alerts after (for `list alerts`)
+- `--theme`: Dashboard theme (for `show` command)
+- `--mcp-server`: Enable MCP server mode (for `show` command)
+- `--color-palette`: Comma-separated hex colors (for `show` command)
+- `--private`: Create private Space (for `sync` command)
+- `--force`: Overwrite existing database (for `sync` command)
+
+## JSON Output Structure
+
+### List Projects
+```json
+{"projects": ["project1", "project2"]}
+```
+
+### List Runs
+```json
+{"project": "my-project", "runs": ["run1", "run2"]}
+```
+
+### Project Summary
+```json
+{
+  "project": "my-project",
+  "num_runs": 3,
+  "runs": ["run1", "run2", "run3"],
+  "last_activity": 100
+}
+```
+
+### Run Summary
+```json
+{
+  "project": "my-project",
+  "run": "my-run",
+  "num_logs": 50,
+  "metrics": ["loss", "accuracy"],
+  "config": {"learning_rate": 0.001},
+  "last_step": 49
+}
+```
+
+### Metric Values
+```json
+{
+  "project": "my-project",
+  "run": "my-run",
+  "metric": "loss",
+  "values": [
+    {"step": 0, "timestamp": "2024-01-01T00:00:00", "value": 0.5},
+    {"step": 1, "timestamp": "2024-01-01T00:01:00", "value": 0.4}
+  ]
+}
+```
+
+### Query Result
+```json
+{
+  "project": "my-project",
+  "query": "SELECT name FROM sqlite_master WHERE type = 'table' ORDER BY name",
+  "columns": ["name"],
+  "rows": [
+    {"name": "alerts"},
+    {"name": "configs"},
+    {"name": "metrics"}
+  ],
+  "row_count": 3
+}
+```
+
+## References
+
+- **Complete CLI documentation**: See [docs/source/cli_commands.md](docs/source/cli_commands.md)
+- **Storage schema and direct SQL**: See [storage_schema.md](storage_schema.md)
+- **API and MCP Server**: See [docs/source/api_mcp_server.md](docs/source/api_mcp_server.md)
+

.agents/skills/trackio/storage_schema.md

@@ -0,0 +1,159 @@
+# Trackio Storage Schema and Direct SQL
+
+Use this reference when you need to inspect Trackio data directly instead of going through higher-level `trackio list` or `trackio get` commands.
+
+## Where Data Is Stored
+
+- Local project databases live in `TRACKIO_DIR`, which defaults to `~/.cache/huggingface/trackio`.
+- Each project is stored in its own SQLite file: `{project}.db`.
+- Media files live under `TRACKIO_DIR/media/`.
+- Parquet files are derived exports written from SQLite for syncing and static Spaces.
+
+## SQLite Tables
+
+Trackio defines its live schema in `trackio/sqlite_storage.py` inside `SQLiteStorage.init_db()`.
+
+### `metrics`
+
+- `id`: integer primary key
+- `timestamp`: ISO timestamp
+- `run_name`: run identifier
+- `step`: integer step
+- `metrics`: JSON text payload
+- `log_id`: optional deduplication key
+- `space_id`: optional pending-sync marker
+
+Indexes:
+
+- `(run_name, step)`
+- `(run_name, timestamp)`
+- unique partial index on `log_id`
+- partial index on `space_id`
+
+### `configs`
+
+- `id`: integer primary key
+- `run_name`: run identifier
+- `config`: JSON text payload
+- `created_at`: ISO timestamp
+
+Constraints:
+
+- unique `run_name`
+- index on `run_name`
+
+### `system_metrics`
+
+- `id`: integer primary key
+- `timestamp`: ISO timestamp
+- `run_name`: run identifier
+- `metrics`: JSON text payload
+- `log_id`: optional deduplication key
+- `space_id`: optional pending-sync marker
+
+Indexes:
+
+- `(run_name, timestamp)`
+- unique partial index on `log_id`
+- partial index on `space_id`
+
+### `project_metadata`
+
+- `key`: primary key
+- `value`: metadata value
+
+### `pending_uploads`
+
+- `id`
+- `space_id`
+- `run_name`
+- `step`
+- `file_path`
+- `relative_path`
+- `created_at`
+
+### `alerts`
+
+- `id`
+- `timestamp`
+- `run_name`
+- `title`
+- `text`
+- `level`
+- `step`
+- `alert_id`
+
+Indexes:
+
+- `run_name`
+- `timestamp`
+- unique partial index on `alert_id`
+
+## Parquet Layout
+
+Trackio flattens JSON blobs when exporting parquet:
+
+- `{project}.parquet` comes from `metrics`
+- `{project}_system.parquet` comes from `system_metrics`
+- `{project}_configs.parquet` comes from `configs`
+
+Static export layout:
+
+- `metrics.parquet`
+- `aux/system_metrics.parquet`
+- `aux/configs.parquet`
+- `runs.json`
+- `settings.json`
+
+The flattened parquet files keep structural columns such as `timestamp`, `run_name`, and `step`, then add one column per JSON key found in the source payload.
+
+## Direct SQL With The CLI
+
+Use `trackio query` for read-only SQL:
+
+```bash
+trackio query project --project my-project --sql "SELECT name FROM sqlite_master WHERE type = 'table' ORDER BY name" --json
+trackio query project --project my-project --sql "PRAGMA table_info(metrics)"
+trackio query project --project my-project --sql "SELECT run_name, MAX(step) AS last_step FROM metrics GROUP BY run_name ORDER BY last_step DESC"
+```
+
+Remote query works too:
+
+```bash
+trackio query project --project my-project --sql "SELECT COUNT(*) AS num_alerts FROM alerts" --space username/my-space --json
+```
+
+`trackio query` accepts read-only `SELECT`, `WITH`, and safe schema `PRAGMA` queries.
+
+## Common Query Patterns
+
+Recent alerts:
+
+```bash
+trackio query project --project my-project --sql "SELECT timestamp, run_name, level, title, step FROM alerts ORDER BY timestamp DESC LIMIT 20"
+```
+
+Latest step per run:
+
+```bash
+trackio query project --project my-project --sql "SELECT run_name, MAX(step) AS last_step FROM metrics GROUP BY run_name ORDER BY last_step DESC"
+```
+
+Recent configs:
+
+```bash
+trackio query project --project my-project --sql "SELECT run_name, created_at, config FROM configs ORDER BY created_at DESC"
+```
+
+Schema inspection:
+
+```bash
+trackio query project --project my-project --sql "PRAGMA index_list(metrics)"
+```
+
+## Agent Guidance
+
+- Start with `trackio list projects --json` if you do not know the project name yet.
+- Use `trackio get` for common summaries and metric retrieval.
+- Fall back to `trackio query` when you need one-off aggregates, joins, or schema introspection.
+- Prefer `--json` when another agent or script needs to consume the result.

.codex/skills/openenv-cli

@@ -0,0 +1 @@
+../../.agents/skills/openenv-cli

.codex/skills/trackio

@@ -0,0 +1 @@
+../../.agents/skills/trackio