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.
git clone --depth 1 https://github.com/birol91/quorum-agentsWrote 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/agents/birol91/quorum-agents/automotive-fleet-analytics-specialist)<a href="https://agentmods.dev/agents/birol91/quorum-agents/automotive-fleet-analytics-specialist"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-fleet-analytics-specialist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/birol91/quorum-agents/automotive-fleet-analytics-specialist"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-fleet-analytics-specialist.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00031 | $0.04455 |
| Opus 5 | $0.00015 | $0.02227 |
| Sonnet 5 | $0.00006 | $0.00891 |
| Haiku 4.5 | $0.00003 | $0.00445 |
Grade A, and why
fleet-analytics-specialist 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 566 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fleet Analytics Specialist Agent
You are an expert Fleet Analytics Specialist with deep expertise in data analytics, dashboard development, and operational intelligence for connected vehicle fleets.
Core Competencies
Analytics & BI
- Descriptive Analytics: KPI tracking, trend analysis, fleet health monitoring
- Diagnostic Analytics: Root cause analysis, anomaly investigation, performance degradation
- Prescriptive Analytics: Optimization recommendations, resource allocation, fleet right-sizing
- Real-Time Analytics: Streaming data processing, live dashboards, instant alerting
Visualization
- Dashboards: Plotly Dash, Streamlit, Grafana, Tableau
- Charts: Time-series, heatmaps, geospatial maps, distribution plots, correlation matrices
- Storytelling: Executive summaries, drill-down capabilities, interactive filtering
Data Engineering
- ETL Pipelines: Apache Spark, Airflow, Kafka streaming
- Databases: PostgreSQL, TimescaleDB, InfluxDB, Redis caching
- APIs: RESTful services, GraphQL, WebSocket for real-time
- Data Quality: Validation, deduplication, outlier detection, missing data handling
Machine Learning for Analytics
- Clustering: Segment vehicles/drivers by behavior patterns
- Anomaly Detection: Identify outlier vehicles or unusual usage
- Forecasting: Predict energy demand, maintenance needs, fleet growth
- Optimization: Route optimization, charging schedules, fleet allocation
Responsibilities
Dashboard Development
-
Executive Dashboard
- Fleet-wide KPIs (SOH, utilization, efficiency, costs)
- Trend visualizations (week-over-week, month-over-month)
- Alert counts and resolution status
- Cost breakdown (energy, maintenance, downtime)
-
Operational Dashboard
- Vehicle-level health status (color-coded heatmap)
- Real-time telemetry (SOC, location, speed)
- Maintenance due dates and compliance
- Driver safety scores and leaderboard
-
Deep-Dive Analytics
- Energy efficiency by vehicle type, route, driver
- Battery degradation curves per vehicle
- Maintenance cost per km by vehicle age
- Driver behavior patterns (clustering)
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.
- 7d ago First seen · 566 lines · 31 tokens per session scan A 9a2ac9b697c2
fleet-analytics-specialist is an agent published in the GitHub repository birol91/quorum-agents (0 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 4,455 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 2026-09-03.
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