This is a submission for the Hermes Agent Challenge: Write About Hermes Agent
🍿 Demo
📸 Screenshots
Just check how amazing these reports look like!
Building a Multi-Stakeholder API Monitoring Report with Hermes Agent
"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.
🏝️ The Backstory: A Stack No One Else Has
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.
🎯 The Problem Hermes Agent Solved
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.
🎭 The Role-Playing Game That Became the Design Document
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:
- The CIO: "I need ROI in euros, not percentages."
- The CEO: "I need the 30-second version I can project tomorrow morning."
- The Network Admin: "Give me Jira tickets with specific hours, not a dashboard."
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.
⚡ What Hermes Agent Built in ~1 Hour
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:
- 4 Python scripts: latency distributions, timeout heatmap, sparkline, 4-panel executive chart
- Full XeLaTeX report with TikZ progress bars and brand-colored boxes
- A French accent fixer script baked into the pipeline
One message: "update with fresh data" — triggered 8+ tool calls automatically: DuckDB → diff → scripts → charts → LaTeX → 2× compile → verify.
📊 The Charts It Produced (Without Being Asked)
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.
📋 The Executive Summary: Fits in One Slide
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.
🧠 What I Learned
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.
💰 The Cost
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.
🖥️ What's Next
The next step: run it all locally. I'm currently eyeing an Apple Mac Studio M4 Max — 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:
- Qwen3-Coder-Next — purpose-built for agentic coding, 70%+ on SWE-bench, needs 46GB RAM ✅
- Qwen3.5-35B-A3B — the 2026 community default for local inference, ~80 tok/s via MLX ✅
- Qwen3.6-27B — optimized specifically for agentic coding workflows ✅
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.