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 research-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/research-agent)<a href="https://agentmods.dev/skills/aws-samples/sample-strands-agent-with-agentcore/research-agent"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agent-with-agentcore/research-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/research-agent"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agent-with-agentcore/research-agent.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 | $0.00050 | $0.00908 |
| Opus 5.5 | $0.00020 | $0.00363 |
| Sonnet 5.5 | $0.00010 | $0.00182 |
| Haiku 4.5 | $0.00005 | $0.00091 |
Grade A, and why
research-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 2mo 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Agent
Autonomous research agent that plans, searches across the web, synthesizes findings, and returns a structured markdown report with citations and charts.
When to use — ALL of these require explicit user intent or clear analytical need
- The user explicitly asks for "research", "report", "analysis", "deep dive", or "investigate"
- The user needs data visualization — charts, graphs, trend plots
- Quantitative or comparative analysis across multiple data points (market sizing, benchmarking, statistical comparisons)
- Multi-section structured reports (literature reviews, competitive analyses, technology surveys)
When NOT to use — default to simpler tools first
- General conversation, Q&A, or factual questions — answer directly
- A single lookup that
wikipedia_searchorgoogle_web_searchcan resolve - Summarizing a single article or URL — use
fetch_url_contentinstead - Code-related tasks — use the
code-agentskill - Browser automation — use the
browser-automationskill - Email, calendar, or other tool-based tasks — use the appropriate skill directly
Important: When in doubt, do NOT delegate to research-agent. Use google_web_search or other tools directly. Only escalate to research-agent when the task clearly requires multi-source synthesis, structured reporting, or chart generation.
How to invoke
Call the research_agent tool with a single plan argument. The plan is free-form prose; include:
- Objectives — what the user is trying to learn or decide
- Topics — the specific angles / subtopics to cover
- Structure — the section layout you want in the final report
Example:
research_agent(plan="""
Research Plan: AI Code Assistant Market 2026
Objectives:
- Current market size and growth trends
- Leading products and differentiators
- Enterprise adoption barriers
Topics:
1. Global market statistics and forecasts
2. Top products (Copilot, Cursor, Claude Code, etc.) and positioning
3. Pricing models and enterprise SKUs
4. Security/compliance concerns raised by buyers
Structure:
- Executive Summary (3-5 bullets)
- Market Overview
- Product Landscape
- Enterprise Adoption
- Outlook
""")
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.
- 2mo ago First seen · 89 lines · 50 tokens per session scan A a0448d339500
research-agent is a skill published in the GitHub repository aws-samples/sample-strands-agent-with-agentcore (197 stars, last pushed 5d ago), licensed MIT. It adds 50 tokens to every session and 908 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.
research-agent compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| research-agentaws-samples/sample-strands-agent-with-agentcore | Skill | 197 | 5d ago | MIT | A | 50 | Claude Code, Codex |
| mk:agent-browserngocsangyem/MeowKit | Skill | 15 | 5d ago | MIT | A | 114 | Claude Code |
| draw-imageai-sns/ai-sns | Skill | 323 | 3mo ago | MIT | A | 67 | Claude Code, Codex |
| governed-postgres-agentaws-samples/sample-pellier-agentic-search-apg | Skill | 12 | yesterday | MIT | A | 54 | Claude Code, Codex |
| care-and-returnsaws-samples/sample-pellier-agentic-search-apg | Skill | 12 | yesterday | MIT | A | 29 | Claude Code, Codex |
| evidenceaws-samples/sample-pellier-agentic-search-apg | Skill | 12 | yesterday | MIT | A | 38 | Claude Code, Codex |
| giftsaws-samples/sample-pellier-agentic-search-apg | Skill | 12 | yesterday | MIT | A | 0 | Claude Code, Codex |