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# %% [markdown]
# # Parameterized Agent Task: System Health Check
#
# This notebook demonstrates how an LLM agent can generate a task notebook,
# a scheduler can parameterize and execute it via papermill,
# and the output becomes a persistent audit artifact.

# %% tags=["parameters"]
# Default parameters — papermill will inject overrides here
threshold = 1.0
hostname = "localhost"

# %%
import json, subprocess, datetime
gather_time = datetime.datetime.now().isoformat()
load_avg = subprocess.check_output(["cat", "/proc/loadavg"]).decode().strip()
load_values = [float(x) for x in load_avg.split()[:3]]
avg_load = sum(load_values) / len(load_values)
intervention_needed = avg_load > threshold
report = {
    "hostname": hostname,
    "threshold": threshold,
    "avg_load": round(avg_load, 3),
    "intervention_needed": intervention_needed,
    "gathered_at": gather_time
}
print(json.dumps(report, indent=2))