Add blog post: AI Agent-Driven Executive Reports with Quarto

content/blog/hermes-quarto-helia-executive-report/index.md

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+---
+title: "AI Agent-Driven Executive Reports with Quarto: A Mobile Analytics Case Study"
+date: 2026-06-03
+people:
+  - Adrien Sales
+description: >
+  How I used the HERMES agent (Qwen 3.7 Max via OpenRouter) to drive Quarto and generate
+  multi-stakeholder executive reports from DuckDB mobile consumption data — including
+  role-playing simulation to tailor the report by persona (CEO, CIO, sysadmin, programmer).
+image: "images/featured.png"
+image-alt: >-
+  A Quarto-generated PDF executive report showing API availability KPIs, a sparkline chart,
+  and annotated latency charts for OPT-NC mobile data — produced by the HERMES AI agent.
+topics:
+  - Artificial Intelligence
+  - Publishing
+software:
+  - quarto
+languages: []
+source: quarto
+tags:
+  - ai-agents
+  - duckdb
+  - executive-report
+  - hermes
+  - openrouter
+---
+
+What if an AI agent could not only answer questions about your data — but also decide *how*
+to present those findings to a CEO, a CIO, and a sysadmin, and style the report accordingly?
+That's exactly what happened when I entered the [HERMES Dev Challenge](https://dev.to/adriens/i-reverse-engineered-my-mobile-operators-apk-then-hermes-agent-wrote-the-executive-report-2j3o)
+with my [Helia Monitor](https://github.com/adriens/helia) project.
+
+## The data setup
+
+[OPT-NC](https://www.opt.nc) is the telecom and postal operator of New Caledonia.
+Their mobile offer, Helia, ships an Android app — but it only shows current consumption,
+no history. I reverse-engineered the APK to extract the private HTTP calls, then built
+a Go CLI that snapshots voice/data/SMS into a local **DuckDB** database every five minutes.
+
+The result: a personal data lakehouse on my laptop, with months of mobile consumption
+history, API availability timings, and latency metrics — data the official app never
+surfaces.
+
+## Entering the HERMES Dev Challenge
+
+[HERMES](https://github.com/nixiesearch/hermes) is an open-source AI agent framework.
+The Dev.to challenge invited participants to push HERMES to its limits.
+My angle: skip the usual chatbot demo and go straight to *executive reporting* — have the
+agent analyze my Helia data and produce a publication-quality PDF, multi-stakeholder,
+with styled charts.
+
+For the model, I chose **Qwen 3.7 Max via [OpenRouter](https://openrouter.ai/)** — a
+frontier open model I had never used before. Everything in the video is genuine first-time
+discovery: no rehearsal, no cherry-picked prompts.
+
+## From AsciiDoc to Quarto
+
+The first agent-generated report came out as AsciiDoc. Functional, but not what I wanted.
+I then switched the challenge target: could HERMES drive **Quarto** to produce something
+print-ready?
+
+The answer was yes — and faster than expected.
+
+HERMES autonomously:
+
+1. Discovered my pre-built DuckDB views (`voice_trend`, `api_availability_kpi`, etc.)
+2. Wrote the Quarto source, wiring each section to a DuckDB SQL query
+3. Rendered the PDF and iterated on styling and theming
+4. Annotated the charts — including a bimodal distribution of API response times it
+   flagged without being asked
+
+{{< video src="https://www.youtube.com/watch?v=Zw-lfNFA0fQ" width="600" >}}
+
+Here is a shorter clip (2'30") showing HERMES annotating SLAs analytics in real time —
+patching the Quarto source with fresh DuckDB data and running a textual analysis
+on timeout patterns:
+
+{{< video src="https://www.youtube.com/watch?v=wUKko5sRwzQ" width="600" >}}
+
+## Role-playing simulation to tailor the report
+
+The most unexpected part of the session: role-playing.
+
+I asked HERMES to re-read the report *as* a CEO, then as a CIO, then as a sysadmin,
+then as a programmer — and to suggest improvements from each perspective. Each pass
+surfaced a genuinely different set of issues:
+
+- **CEO**: "Too many raw numbers. Give me a traffic-light summary."
+- **CIO**: "Where is the SLA breach risk? Which service degraded first?"
+- **Sysadmin**: "Show me the timeout distribution by hour-of-day, not by day."
+- **Programmer**: "The sparkline query doesn't handle NULL gaps correctly."
+
+The agent self-improved across four passes, and the final PDF was structurally different
+from the first draft — without me writing a single line of Quarto myself.
+
+## What I discovered in the data
+
+Two findings emerged that I hadn't pre-wired into any view:
+
+1. **Bimodal distribution of API response times** — HERMES spotted a clear two-peak
+   distribution in the latency histogram and labeled it in the chart automatically.
+2. **Hour-of-day timeout pattern** — a heatmap (GitHub contribution-style) of timeout
+   counts by day × hour revealed a recurring early-morning degradation window.
+
+Both appeared because the agent was free to query DuckDB directly, not just read
+pre-computed summaries.
+
+## Why Quarto was the right output format
+
+I could have asked for a plain Markdown report or a CSV summary. I chose Quarto because:
+
+- **PDF rendering** is first-class: `quarto render` produces a print-ready document
+  with no extra tooling.
+- **Parameterization** is natural: each stakeholder section became a Quarto callout or
+  tabset, separating audiences within one source file.
+- **Theming** is straightforward: HERMES applied a custom SCSS theme and adjusted the
+  logo placement in one pass.
+- **Portability**: the `.qmd` source + DuckDB file is the complete reproducible artifact.
+  Anyone with Quarto and the database can re-render the full report.
+
+The agent never needed to know *how* Quarto works internally — just that
+`quarto render index.qmd` produces a PDF. The declarative nature of Quarto's
+frontmatter and chunk syntax is exactly what makes it agentic-friendly.
+
+## Results and cost
+
+- **17-page executive PDF**, three stakeholder sections (CEO / CIO / Network Admin)
+- **326 LLM requests**, 61.4M tokens
+- **$19.57 total cost** on Qwen 3.7 Max via OpenRouter
+- Development time: one session, roughly 85 minutes end-to-end (watch the full video above)
+
+For comparison: a consulting firm would charge at minimum a week of work for a comparable
+deliverable. The agent produced a first draft in under 20 minutes.
+
+## Try it yourself
+
+- Full article and context: [Dev.to post](https://dev.to/adriens/i-reverse-engineered-my-mobile-operators-apk-then-hermes-agent-wrote-the-executive-report-2j3o)
+- Source repo: [github.com/adriens/helia](https://github.com/adriens/helia)
+- Live demo (85 min): [YouTube](https://youtu.be/Zw-lfNFA0fQ)
+
+The complete stack — Go CLI + DuckDB + HERMES + Quarto — is open source.
+If you have a data source with an API (or a reverse-engineered one), the same pipeline
+should work for any periodic consumption or availability dataset.