⚚ I reverse-engineered my mobile operator's APK — then Hermes Agent wrote the executive report

A developer in New Caledonia reverse-engineered the APK of OPT-NC's Helia mobile app, extracted its private HTTP calls, and built a Go CLI that snapshots voice, data, and SMS consumption every five minutes into a local DuckDB database. The developer then used Hermes Agent to generate a 17-page professional executive report—complete with brand-colored charts, a CEO-ready dashboard, and actionable network admin tickets—for a total cost of $19.57.

This is a submission for the Hermes Agent Challenge: Write About Hermes Agent // Detect dark theme var iframe = document.getElementById 'tweet-2059698327235805258-252' ; if document.body.className.includes 'dark-theme' { iframe.src = "https://platform.twitter.com/embed/Tweet.html?id=2059698327235805258&theme=dark" } Just check how amazing these reports look like "Just generate a PDF" — famous last words. What started as a simple request turned into something much bigger: a full monitoring stack for my mobile operator, built evenings and weekends, culminating in a 17-page professional report that would have taken a full week to build manually. Total cost with Hermes Agent: $19.57 . I'm Adrien, a developer in New Caledonia. OPT-NC's Helia mobile service has an app — but no public API, no CLI, nothing on any marketplace. So I reverse-engineered the APK , extracted the private HTTP calls, and rebuilt them in a Go CLI that snapshots voice, data, and SMS consumption every 5 minutes into a local DuckDB database. Then I built KDE Plasma widgets in Python/PyQt that read from DuckDB and display live on my desktop — mirroring the official app's data, but with history, trends, burn rate, and alerts. Plus a system tray icon showing live API status at a glance. The official app shows you now . My stack shows you now, history, trends, and alerts. No other Helia customer has this. That's the breakthrough. All this data was sitting in DuckDB. The question was: how do I present it to people who don't speak SQL? Three completely different audiences: the CEO who needs a 30-second summary screenshot-ready for PowerPoint, the CIO who wants ROI in euros and SLA compliance, and the Network Admin who needs actionable tickets with specific hours and error patterns. Before writing a single line of code, I asked Hermes Agent to do something unusual: simulate a full team meeting with 7 personas — CEO, CIO, network admin, developers, and marketing. It produced a full transcript. Each persona argued their case: That transcript became the design document. Every page of the report was written against a specific person's stated need. No guessing. No generic output. It started with the data. No assumptions — it queried the schema and immediately caught something: average latency was 2,534ms but the median was 204ms. Bimodal distribution. That single insight shaped every chart. It extracted brand colors from the website before writing a single line of LaTeX. Hermes Agent opened Helia's site, pulled the magenta/pink gradient from the SVG logo, and used it consistently across every chart, table, and tcolorbox. Small detail. Big difference. Then it built everything: One message: "update with fresh data" — triggered 8+ tool calls automatically: DuckDB → diff → scripts → charts → LaTeX → 2× compile → verify. I asked for charts. I didn't ask for this : Latency distribution — median/mean/P95 lines labeled, shaded fast vs slow zones, annotated arrow pointing to the long tail: "Queue longue timeout ~12s ~40% des pings " . Log-scale version revealing the true bimodal structure: two peaks at ~80ms and ~4s. 4-panel executive dashboard — availability gauge 87.2% vs 99.5% SLA , latency 2534ms vs 500ms — "5.1x trop lent" , timeout rate "1 requête sur 8 échoue" , composite SLA score per metric. Score global: 65%. Verdict: RED. Timeout heatmap — all 18 timeouts concentrated on Wednesday evening 19h–22h. The rest of the week: clean. Instant actionable insight for the network admin. All in Helia brand colors. All annotated. None of it explicitly requested. Page 3 of the report is designed to be screenshotted directly into PowerPoint. Verdict box at the top red , plain-language translation "1 call in 8 fails" , business impact in euros, top 3 problems with responsible parties. The CEO gets it in 30 seconds. Orchestration is the real superpower. I asked for a PDF. It fetched brand colors, queried the DB, wrote Python scripts, compiled LaTeX — all unprompted. Iteration is the default. The first charts were basic. The final ones have annotated thresholds, color-coded data points, and statistical summaries. That's the loop. Skills are the real ROI. Everything got distilled into a reusable ~/.claude/skills/reporting-latex/ skill. Next similar project starts at 80%, not zero. Qwen3.7-Max via OpenRouter. Alibaba's flagship agentic model, built for long-horizon autonomous execution. 326 requests. 61.4M tokens. $19.57. ~1 hour. vs a full week manually. The next step: run it all locally . I'm currently eyeing an Apple Mac Studio M4 Max https://www.ldlc.com/fiche/PB00675416.html — 16-core CPU, 40-core GPU, 64 Go unified memory. New Caledonia is 20,000km from everything; local inference just makes sense. Zero API costs, zero latency to the cloud, full control. With 64GB unified memory, I'd be able to run: The same class of model as Qwen3.7-Max on OpenRouter — locally, for free, forever. A fully local Hermes Agent stack. From $19.57 on OpenRouter to owning the hardware. That's the roadmap. 🇳🇨 The pattern: monitor → query → visualize → compose → translate . The translate step — turning a percentile into a story a CEO can act on — is where Hermes Agent earns its keep. Have you used Hermes Agent for multi-tool orchestration? Curious how your experience compares.