Sample Strands Agent with Amazon Bedrock AgentCore is an end-to-end reference architecture for building multi-agent chatbots on AWS. Teams use it to explore agent orchestration, tool execution, memory, browser automation, and agent-to-agent collaboration with Strands Agents and Bedrock AgentCore.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aws-samples/sample-strands-agent-with-agentcore --skill visualizationgit clone --depth 1 https://github.com/aws-samples/sample-strands-agent-with-agentcoreWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aws-samples/sample-strands-agent-with-agentcore/visualization)<a href="https://agentmods.dev/skills/aws-samples/sample-strands-agent-with-agentcore/visualization"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agent-with-agentcore/visualization/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aws-samples/sample-strands-agent-with-agentcore/visualization"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agent-with-agentcore/visualization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.00770 |
| Opus 5.5 | $0.00011 | $0.00308 |
| Sonnet 5.5 | $0.00005 | $0.00154 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
visualization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visualization
When to Use This Skill
Use create_visualization for interactive in-app charts of numerical data.
For an explicit PNG or PDF deliverable, use the visual-design skill instead. This tool returns a chart specification, not a downloadable image file. If the requested chart needs controls absent from this schema, such as fixed axis bounds, choose a tool that supports them rather than dropping the requirement.
| Use this skill for... | Use excalidraw skill for... |
|---|---|
| Sales figures by quarter | System architecture diagram |
| Survey response percentages | Flowchart or decision tree |
| Stock price over time | Sequence / interaction diagram |
| Market share breakdown | Mind map or concept map |
| Any x/y or segment/value data | Shapes, boxes, arrows, labels |
Available Tool
- create_visualization: Create a chart specification for frontend rendering.
Parameters (MUST match exactly)
| Parameter | Type | Required | Description |
|---|---|---|---|
chart_type |
str | Yes | "bar", "line", or "pie" |
data |
list[dict] | Yes | Array of data objects — see formats below |
title |
str | No | Chart title |
x_label |
str | No | X-axis label (bar/line only) |
y_label |
str | No | Y-axis label (bar/line only) |
Data Formats (CRITICAL — use exact field names)
Bar / Line charts — each object MUST have "x" and "y" keys:
[{"x": "Jan", "y": 100}, {"x": "Feb", "y": 150}, {"x": "Mar", "y": 120}]
Pie charts — each object MUST have "segment" and "value" keys:
[{"segment": "Category A", "value": 30}, {"segment": "Category B", "value": 70}]
Optional: add "color": "hsl(210, 100%, 50%)" to any data point for custom color.
Example tool_input
Bar chart:
{
"chart_type": "bar",
"data": [{"x": "Q1", "y": 250}, {"x": "Q2", "y": 310}, {"x": "Q3", "y": 280}],
"title": "Quarterly Revenue",
"x_label": "Quarter",
"y_label": "Revenue ($K)"
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +1 lines · +9 tokens per session 922b9f6a466c
- 1mo ago First seen · 79 lines · 18 tokens per session scan A 1d04fa703d1f
visualization is a skill published in the GitHub repository aws-samples/sample-strands-agent-with-agentcore (195 stars, last pushed 3d ago), licensed MIT. It adds 27 tokens to every session and 770 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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