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 agentmods add skills/aws-samples/sample-strands-agent-with-agentcore/web-searchnpx skills add aws-samples/sample-strands-agent-with-agentcore --skill web-searchgit 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/web-search)<a href="https://agentmods.dev/skills/aws-samples/sample-strands-agent-with-agentcore/web-search"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-strands-agent-with-agentcore/web-search.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00021 | $0.00467 |
| Opus 5 | $0.00010 | $0.00234 |
| Sonnet 5 | $0.00004 | $0.00093 |
| Haiku 4.5 | $0.00002 | $0.00047 |
Grade A, and why
web-search 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 5d 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.
What it actually says
Web Search
Available Tools
- ddg_web_search(query, max_results=5): Search DuckDuckGo and return results with title, snippet, and link.
- fetch_url_content(url, include_html=False, max_length=50000): Fetch a URL and extract clean text content.
Parameters
ddg_web_search
| Parameter | Type | Default | Description |
|---|---|---|---|
query |
str | (required) | Search query string |
max_results |
int | 5 | Number of results (max 10) |
fetch_url_content
| Parameter | Type | Default | Description |
|---|---|---|---|
url |
str | (required) | URL to fetch (must start with http:// or https://) |
include_html |
bool | False | Include raw HTML in response |
max_length |
int | 50000 | Maximum character length of extracted text |
Usage Guidelines
- Use specific, targeted search queries for best results
- Set max_results to 3-5 for focused searches, up to 10 for broad research
- Use fetch_url_content to read full page content from search result links
- Break complex research into multiple targeted queries rather than one broad query
- fetch_url_content automatically strips navigation, scripts, and boilerplate HTML
- Reduce max_length for quick summaries or when you only need the beginning of a page
Citation Format
When presenting information from search results or fetched pages, wrap every specific claim in <cite> tags:
<cite source="SOURCE_TITLE" url="URL">claim text</cite>
Rules:
- Cite factual claims, statistics, quotes, and specific information from search results.
- The
sourceattribute should contain the title or name of the source. - The
urlattribute should contain the source URL when available. - Do NOT cite your own reasoning or general knowledge.
- If search results don't contain relevant information, inform the user rather than guessing.
- Use the minimum number of citations necessary to support claims.
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.
- 5d ago First seen · 50 lines · 21 tokens per session scan A 49f6da8a3d2a
web-search is a skill published in the GitHub repository aws-samples/sample-strands-agent-with-agentcore (192 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 467 once invoked, about $0.0001 per session on Opus 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.
Other skills, from other repositories
draw-image
Generate an image from a text prompt using an OpenAI-compatible image generation API (gpt-image-1-mini or compatible). The image is uploaded to the gofile.io public file sharing service and ONLY the public download page URL is returned. Trigger when user asks to draw, paint, generate, or create an image.
A2A JSON-RPC Call
Call a peer agent's A2A JSON-RPC endpoint. Supports tasks/send (send a task message) and tasks/get (query task status).
Fetch Agent Card
Fetch an A2A agent card JSON from a given endpoint URL. Tries direct GET first, then falls back to /.well-known/agent.json.
Echo Skill Sample
Echo input parameters as JSON.
mk:agent-browser
Browser automation CLI for AI agents using agent-browser. Use for navigating websites, clicking/filling pages, screenshots, data extraction, web app testing, exploratory QA, dogfooding, Electron apps, Slack automation, Vercel Sandbox browser runs, AWS AgentCore cloud browsers, auth-heavy flows, and long autonomous…
health-event-impact-assessment
Evaluates AWS Health event impact on application workloads using topology knowledge. Determines blast radius, affected teams, and notification routing. Use this skill when investigating incidents triggered by AWS Health events including scheduled maintenance, operational issues, and service degradation notifications.