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/azure-samples/eshoplite/agentic-modernizationnpx skills add Azure-Samples/eShopLite --skill agentic-modernizationgit clone --depth 1 https://github.com/Azure-Samples/eShopLiteWrote 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/azure-samples/eshoplite/agentic-modernization)<a href="https://agentmods.dev/skills/azure-samples/eshoplite/agentic-modernization"><img src="https://agentmods.dev/badge/skills/azure-samples/eshoplite/agentic-modernization.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 | $0.00033 | $0.00278 |
| Opus 5 | $0.00016 | $0.00139 |
| Sonnet 5 | $0.00007 | $0.00056 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
agentic-modernization 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 4d 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
Context
Use this skill when a modernization story needs to move from "the app is upgraded" to "the app is now useful to agents and operators." It applies when you are planning demos or docs around observability, search grounding, store intelligence reports, safe tools, or agent collaboration.
Patterns
- Start with the modernized app foundation: telemetry, deployability, and clear service boundaries.
- Keep the live demo local-first; treat hosted agents as an extension path.
- Reuse existing app capabilities as the source of truth for AI outputs.
- Split agent stories into focused responsibilities: observability, discovery, reporting, and orchestration.
Examples
- Scenario 13: Observability Assistant with Foundry Local
- Scenario 16: MCP Store Operations Tools
- Scenario 17: A2A Store Operations Network
Anti-Patterns
- Adding a generic chatbot that is not grounded in the app.
- Pitching Hosted Agents as the core demo before the local path works.
- Letting AI invent products, traces, or business signals.
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.
- 4d ago First seen · 29 lines · 33 tokens per session scan A 4e1406588c14
agentic-modernization is a skill published in the GitHub repository Azure-Samples/eShopLite (168 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 278 once invoked, about $0.0002 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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