code-interpreter

name	code-interpreter
description	Write and run real Python in a secure sandbox to answer any smart-home question that is better solved by *computing* than by reasoning — energy/telemetry data analysis, optimization (e.g. price-aware HVAC schedules), statistical anomaly detection, Monte-Carlo cost simulation, charting. Use this skill WITHOUT waiting for the user to say "run code" — if the answer needs aggregation, math, a simulation, or a chart over device data, call `execute_python`.
allowed-tools	execute_python

Code Interpreter

You have a secure Amazon Bedrock AgentCore Code Interpreter sandbox available through the execute_python tool. It runs Python with the scientific stack pre-installed (pandas, numpy, matplotlib, scipy, ...). State persists between calls within a turn, so you can build up an analysis across several blocks. The user watches each block run live in the CodeInterpreter side panel — your code, its streaming output, and any charts you generate.

Call execute_python on your own initiative whenever the answer is better computed than reasoned, even if the user doesn't mention code.

When to call (call execute_python for any of these without asking)

• "Analyze my home's energy use this week and chart the trend." → load/synthesize the telemetry into a pandas DataFrame, aggregate, plot with matplotlib.
• "What's the cheapest way to run my AC given time-of-use pricing?" → set up the price curve and comfort constraints, compute an optimal schedule, report the savings and plot it.
• "Are there anomalies in my fan's power readings?" → run Z-score / rolling-stats anomaly detection over the series and plot the flagged windows.
• "How much might my electricity bill vary next month?" → Monte-Carlo simulate the bill distribution under a usage policy and plot the histogram + confidence band.
• Any request involving aggregation, statistics, optimization, simulation, forecasting, or "chart / plot / graph this".

How to call

• execute_python(code=<python>, title=<short human label>). The title is shown as the step header in the panel (e.g. "Aggregate daily energy", "Plot savings").
• Break a non-trivial analysis into a few focused blocks — load/prepare, compute, then plot — calling execute_python once per block. State (variables, imports, DataFrames) carries over between calls, so later blocks can use earlier results.
• To produce a chart, use matplotlib and save it to a file (e.g. plt.savefig("chart.png")). Saved images are surfaced inline in the panel and in the Files tab. Always label axes and add a title.
• Chart text must be English / ASCII — titles, axis labels, legends, tick labels, and annotations. The sandbox has no font that can render Chinese (or other non-Latin scripts) together with Latin/digits, so CJK chart text comes out as blank "tofu" boxes. Write all in-chart text in English even when the conversation and your chat reply are in Chinese (e.g. title "Weekly Home Energy (kWh)", not "每周家庭能耗"). Your chat reply to the user stays in their language — only the text drawn inside the image must be ASCII.
• Do not put emoji (e.g. 🏠 📊 🍕) in chart titles or labels either — no sandbox font contains them, so they render as blank boxes. Emoji are fine in your chat reply, just not inside the chart.
• When you lack real device data, synthesize a realistic dataset in code (clearly noted as synthetic) so the demonstration still runs end-to-end. State in your reply that the data was synthesized.
• print(...) anything you want the user to see as text output.

After the tool returns

• The tool returns a short text summary (stdout tail, chart count). Paraphrase the actual computed result in your reply — do not invent numbers that weren't in the output.
• If the tool returns an error (non-zero exit / traceback), read the error, fix the code, and call execute_python again. Do not fabricate a result.

When NOT to call

• Device control / cooking / LED commands — use the dedicated device-control skills.
• Live website lookups — use browse_web.
• Enterprise document lookups — use query_knowledge_base.
• Simple facts or chit-chat you can answer directly — no sandbox needed.