This is a submission for the Hermes Agent Challenge: Write About Hermes Agent
πΏ Demo
πΈ Screenshots
Just check how amazing these reports look like!
Building a Multi-Stakeholder API Monitoring Report with Hermes Agent
"Just generate a PDF" β 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.
ποΈ 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 β 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 β 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.
π― 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.
π 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 β 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.
β‘ What Hermes Agent Built in ~1 Hour
It started with the data. No assumptions β 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" β triggered 8+ tool calls automatically: DuckDB β diff β scripts β charts β LaTeX β 2Γ compile β verify.
π The Charts It Produced (Without Being Asked)
I asked for charts. I didn't ask for this:
Latency distribution β 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 β availability gauge (87.2% vs 99.5% SLA), latency (2534ms vs 500ms β "5.1x trop lent"), timeout rate ("1 requΓͺte sur 8 Γ©choue"), composite SLA score per metric. Score global: 65%. Verdict: RED.
Timeout heatmap β all 18 timeouts concentrated on Wednesday evening 19hβ22h. 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.
π 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.
π§ 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 β 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.
π° 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.
π₯οΈ What's Next
The next step: run it all locally. I'm currently eyeing an Apple Mac Studio M4 Max β 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 β purpose-built for agentic coding, 70%+ on SWE-bench, needs 46GB RAM β
- Qwen3.5-35B-A3B β the 2026 community default for local inference, ~80 tok/s via MLX β
- Qwen3.6-27B β optimized specifically for agentic coding workflows β
The same class of model as Qwen3.7-Max on OpenRouter β locally, for free, forever. A fully local Hermes Agent stack.
From $19.57 on OpenRouter to owning the hardware. That's the roadmap. π³π¨
The pattern: monitor β query β visualize β compose β translate. The translate step β turning a percentile into a story a CEO can act on β is where Hermes Agent earns its keep.
Have you used Hermes Agent for multi-tool orchestration? Curious how your experience compares.
