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 code-agentgit 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/code-agent)<a href="https://agentmods.dev/skills/aws-samples/sample-strands-agent-with-agentcore/code-agent"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agent-with-agentcore/code-agent/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/code-agent"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agent-with-agentcore/code-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 194 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00047 | $0.02639 |
| Opus 5.5 | $0.00019 | $0.01056 |
| Sonnet 5.5 | $0.00009 | $0.00528 |
| Haiku 4.5 | $0.00005 | $0.00264 |
Grade A, and why
code-agent 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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Agent
An autonomous coding agent. It doesn't just write code on demand — it thinks through problems, forms its own plan, reads the existing codebase to understand context, implements solutions iteratively, and verifies they work before finishing.
Given a goal, it will:
- Explore the workspace to understand what's already there
- Break the task into steps and track them with a todo list
- Implement, run, and iterate until the outcome is correct
- Ask only when it hits a real decision point, not for every micro-step
Brief it like you'd brief a capable engineer: describe what you want to achieve, not how to do it.
Code Agent vs Code Interpreter
| Code Agent | Code Interpreter | |
|---|---|---|
| Nature | Autonomous agent (Claude Code) | Sandboxed execution environment |
| Best for | Multi-file projects, refactoring, test suites | Quick scripts, data analysis, prototyping |
| File persistence | All files auto-synced to S3, accessible via workspace tools | Files in /mnt/workspace persist across interpreter restarts |
| Session state | Files + conversation persist across sessions | Variables persist within one interpreter session; workspace files persist for the chat session |
| Autonomy | Plans, writes, runs, and iterates independently | You write the code it executes |
| Use when | You need an engineer to solve a problem end-to-end | You need to run a specific piece of code |
Execution Environment
The code agent runs in an isolated container dedicated solely to this session. Its filesystem, running processes, and local ports are completely separate from your own environment — do not attempt to access its paths or local servers via browser or other tools.
User-uploaded session files are synchronized from the canonical Workspace
inputs/ prefix before every Code Agent task and are available under
inputs/<filename>. Treat inputs/ as read-only; generated files belong
elsewhere in the Code Agent workspace.
Every code_agent call must include workspace_paths. Pass the exact
inputs/<filename> paths required by the task, or [] when the task does not
use session attachments. The task fails before execution if a required file is
not synchronized; do not ask the Code Agent to reconstruct a missing source.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 First seen · 244 lines · 47 tokens per session scan A aac490e1d2bf
code-agent 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 47 tokens to every session and 2,639 once invoked, about $0.0002 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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