Amazon Bedrock AgentCore Samples is a collection of examples and tutorials for deploying and operating AI agents with Amazon Bedrock AgentCore. Developers use it to integrate agent applications built with different frameworks and language models while learning AgentCore features. The catalogue add-ons provide agent-oriented guidance for working with these samples and services.
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 awslabs/agentcore-samples --skill earnings-snapshotgit clone --depth 1 https://github.com/awslabs/agentcore-samplesWrote 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/awslabs/agentcore-samples/earnings-snapshot)<a href="https://agentmods.dev/skills/awslabs/agentcore-samples/earnings-snapshot"><img src="https://agentmods.dev/badge/skills/awslabs/agentcore-samples/earnings-snapshot.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 5.1 | $0.00026 | $0.00417 |
| Opus 5 | $0.00013 | $0.00209 |
| Sonnet 5 | $0.00005 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
earnings-snapshot 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 7d 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
Earnings Snapshot Skill
Use this skill when a user asks about a company's earnings, valuation metrics, fundamentals, whether a stock is cheap or expensive, or how recent results compared to expectations.
Required workflow
- Retrieve stock data using
get_stock_datafor the requested symbol. - Search for earnings-related news using
search_newswith the stock's sector. - Extract the following fundamental metrics from stock data:
- P/E ratio (compare to sector average: Technology ~34x, Healthcare ~22x, Financials ~13x, Energy ~14x, Consumer Discretionary ~30x, Consumer Staples ~25x)
- Dividend yield (0% = growth stock; >2% = income stock)
- Market cap tier (Mega >$1T, Large $100B-$1T, Mid $10B-$100B)
- Assess valuation:
- P/E > 1.3× sector average → Premium (growth priced in)
- P/E within 0.7×–1.3× sector average → Fair Value
- P/E < 0.7× sector average → Discount (value opportunity or value trap)
- Identify the most relevant earnings headline from news results.
- Provide a 2-sentence earnings outlook.
Output Format
Earnings Snapshot: {SYMBOL} — {Company Name}
Price : ${price}
P/E Ratio : {pe_ratio}x ({Premium | Fair Value | Discount} vs. {sector} avg {sector_avg}x)
Dividend Yield: {yield}%
Market Cap : ${cap} ({tier})
Earnings News : {top headline}
Outlook : {2-sentence assessment}
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.
- 7d ago First seen · 39 lines · 26 tokens per session scan A 17ea0c1c1801
earnings-snapshot is a skill published in the GitHub repository awslabs/agentcore-samples (3,336 stars, last pushed yesterday), licensed Apache-2.0. It adds 26 tokens to every session and 417 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.
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