---
title: 1. Analysis Report Agent
description: Build an agent that goes from data analysis to slide creation and download, using the sandbox's built-in tools and the pptx skill.
sidebar:
order: 1
---
import { Steps, Tabs, TabItem, Aside } from '@astrojs/starlight/components';
import ShareOnX from '../../../../components/ShareOnX.astro';
We will build an agent that analyzes data and produces a slide (PPTX) report. The uv and authentication setup is the same as in [3. Create an Agent with the SDK](/en/intermediate/03_sdk/); we will create a new project for this page and work from there.
On this page, we will use the following Managed Agents features for the first time.
| Feature | Role |
|------|------|
| Built-in tools (`agent_toolset`) | A set of tools for running bash, file operations, web search, and more inside the sandbox |
| Environment `packages` | Configuration that pre-installs apt, pip, and npm packages into the sandbox |
| Skills (`skills`) | A mechanism for teaching the agent specialized workflows such as document creation |
| Session outputs | A mechanism for downloading files the agent saved to `/mnt/session/outputs/` to your local machine |
## 1. Create a Project
Create a project, move into its folder, and install the Claude SDK.
```shell
uv init report-agent
cd report-agent
uv add anthropic
```
## 2. Create the Resources
1. Create `setup_report.py` in the project folder and save the following content.
```python title="setup_report.py"
import json
from anthropic import Anthropic
client = Anthropic()
###############################
# 1. Create the environment (pre-install the pptx skill's dependencies)
###############################
environment = client.beta.environments.create(
name="Report-environment-adv",
config={
"type": "cloud",
"packages": {
"apt": ["libreoffice-impress", "poppler-utils", "fonts-noto-cjk"],
"pip": ["markitdown[pptx]", "Pillow"],
"npm": ["pptxgenjs"],
},
"networking": {"type": "unrestricted"},
},
)
print(f"environment: {environment.id}")
###############################
# 2. Create the agent (full built-in toolset + pptx skill)
###############################
agent = client.beta.agents.create(
name="Report Agent ADV",
model="claude-sonnet-5",
description="An agent that performs data analysis and creates slide reports.",
system="You are a data analysis and report creation assistant. Use the sandbox's bash and Python for analysis, and follow the pptx skill for slide creation. Always save deliverables to /mnt/session/outputs/.",
tools=[{"type": "agent_toolset_20260401", "default_config": {"enabled": True}}],
skills=[{"type": "anthropic", "skill_id": "pptx"}],
)
print(f"agent: {agent.id}")
with open("ids_report.json", "w") as f:
json.dump({"environment_id": environment.id, "agent_id": agent.id}, f, indent=2)
print("Saved IDs to ids_report.json")
```
There are three key points in this configuration.
- **`packages`** — Pre-installs the dependencies required by the [pptx skill definition](https://github.com/anthropics/skills/blob/main/skills/pptx/SKILL.md) (LibreOffice, Poppler, markitdown, pptxgenjs) plus Japanese fonts. apt, cargo, gem, go, npm, and pip are supported, and packages are cached across sessions that use the same environment
- **`agent_toolset_20260401`** — The full set of built-in tools: bash, read/write/edit, glob/grep, and web search/fetch. Unlike the MCP tools we used so far, these run inside the sandbox
- **`skills`** — Anthropic's prebuilt skills (`pptx`, plus `xlsx`, `docx`, and `pdf`) can be used simply by specifying a `skill_id`
1. Run the script.
```shell
uv run setup_report.py
```
## 3. Have the Agent Create a Report
1. Create `report.py` in the project folder and save the following content.
```python title="report.py"
import json
import pathlib
from anthropic import Anthropic
client = Anthropic()
with open("ids_report.json") as f:
ids = json.load(f)
# Create a session
session = client.beta.sessions.create(
agent=ids["agent_id"],
environment_id=ids["environment_id"],
)
print(f"session: {session.id}")
# Open the stream before sending the task
stream = client.beta.sessions.events.stream(session_id=session.id)
client.beta.sessions.events.send(
session.id,
events=[
{
"type": "user.message",
"content": [
{
"type": "text",
"text": (
"Create a CSV of one year of monthly sales data (units sold and revenue) "
"for a fictional takoyaki shop, and analyze the trends. Then turn the "
"results into a 3-slide PPTX report consisting of a title slide, a sales "
"trend chart, and an analysis summary, and save it to "
"/mnt/session/outputs/report.pptx."
),
}
],
}
],
)
print("Task sent. This will take a few minutes to complete...\n")
for event in stream:
if event.type == "agent.tool_use":
print(f"[tool: {event.name}]")
elif event.type == "agent.message":
for block in event.content:
if block.type == "text":
print(block.text)
elif event.type == "session.status_idle":
if event.stop_reason.type != "requires_action":
break
elif event.type == "session.status_terminated":
break
stream.close()
# Download the deliverables
print("\nChecking the deliverables...")
files = client.beta.files.list(
scope_id=session.id,
betas=["managed-agents-2026-04-01"],
)
for f in files.data:
print(f"- {f.filename} ({f.size_bytes} bytes)")
content = client.beta.files.download(f.id)
out = pathlib.Path(f.filename).name
content.write_to_file(out)
print(f" -> saved to {out}")
```
The final block downloads the deliverables. Files the agent saved to `/mnt/session/outputs/` can be listed and downloaded with the Files API by passing the session ID as `scope_id`.
1. Run the script. The first run takes about 5-10 minutes for sandbox preparation (installing LibreOffice and other packages) and slide creation.
```shell
uv run report.py
```
```text
session: sesn_016pxZpFV5ny8Wj14fU2wVgD
Task sent. This will take a few minutes to complete...
[tool: bash]
The data looks good. Next, I will run the analysis.
[tool: bash]
pptxgenjs is available. I will create the slides with a color palette that suits a takoyaki shop.
[tool: write]
[tool: bash]
Running content QA and visual QA.
...
I will fix two issues: the line chart interpolation (lineSmooth) exaggerates the data, and the gold text on slide 3 has weak contrast.
[tool: edit]
...
I have created the following deliverables.
...
Checking the deliverables...
- report.pptx (26240 bytes)
-> saved to report.pptx
- takoyaki_monthly_sales.csv (344 bytes)
-> saved to takoyaki_monthly_sales.csv
```
1. Open the downloaded `report.pptx` in PowerPoint or a similar app and check the result.
## Summary
- The environment's `packages` setting lets you pre-install apt, pip, and npm packages into the sandbox (cached across sessions that use the same environment).
- Enabling the built-in tools (`agent_toolset`) lets the agent run bash and file operations inside the sandbox.
- **Skills** let you teach the agent specialized workflows like slide creation just by specifying a `skill_id`.
- Deliverables the agent saved to `/mnt/session/outputs/` can be listed and downloaded via the Files API by passing the session ID as `scope_id`.