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.
npx skills add evoelsewhere/evoflux --skill data-analyticsgit clone --depth 1 https://github.com/evoelsewhere/evofluxWrote 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/skills/evoelsewhere/evoflux/data-analytics)<a href="https://agentmods.dev/skills/evoelsewhere/evoflux/data-analytics"><img src="https://agentmods.dev/badge/skills/evoelsewhere/evoflux/data-analytics/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/skills/evoelsewhere/evoflux/data-analytics"><img src="https://agentmods.dev/badge/skills/evoelsewhere/evoflux/data-analytics.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 | $0.00179 | $0.01653 |
| Opus 5.5 | $0.00072 | $0.00661 |
| Sonnet 5.5 | $0.00036 | $0.00331 |
| Haiku 4.5 | $0.00018 | $0.00165 |
Grade A, and why
data-analytics 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 22d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Analytics
Answer quantitative product and business questions with reproducible, source-backed evidence, then deliver the result in the format the user needs.
Route the task
Read only the reference files the task needs, completely, before acting.
| Task | Read |
|---|---|
| A metric moved, missed a target, spiked, or two numbers disagree | references/metric-diagnostics.md |
| A product or business decision: prioritization, segmentation, launch, experiment, tradeoff | references/decision-analysis.md |
| Is a dataset, source, join, dashboard, or metric trustworthy (freshness, grain, duplicates, drift) | references/data-quality.md |
| Define KPIs, metric definitions, drivers, guardrails, targets, or a measurement plan | references/kpi-design.md |
| KPI status update, scorecard, WBR/MBR/QBR, executive readout | references/kpi-reporting.md |
| TAM/SAM/SOM, segment, or opportunity sizing | references/market-sizing.md |
| Review an analysis, notebook, chart, or recommendation before it is shared | references/pre-share-review.md |
| Business definitions, ownership, recent changes, or decision framing are missing | references/business-context.md, before the primary reference |
| Create, revise, or QA a chart or figure | references/visualization.md |
| A durable report (Markdown, HTML, PDF, DOCX, slides), including converting a report to PDF | references/deliverables.md |
| A dashboard or monitoring view (HTML, Streamlit, BI platform) | references/dashboards.md |
| A reproducible SQL/Python Jupyter notebook | references/notebooks.md |
| Save data context, or create, update, inspect, or repair a semantic layer | references/semantic-layer.md |
| Drafting the files of a semantic-layer skill | references/semantic-layer-template.md |
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/demo-product-growth.csv 1.4 KB
- references/business-context.md 3.8 KB
- references/dashboards.md 5.5 KB
- references/data-quality.md 7.3 KB
- references/decision-analysis.md 5.4 KB
- references/deliverables.md 6.1 KB
- references/kpi-design.md 5.1 KB
- references/kpi-reporting.md 7.0 KB
- references/market-sizing.md 4.1 KB
- references/metric-diagnostics.md 5.5 KB
- references/notebooks.md 4.2 KB
- references/pre-share-review.md 7.4 KB
- references/semantic-layer-template.md 5.7 KB
- references/semantic-layer.md 12 KB
- references/visualization.md 3.0 KB
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.
- 22d ago Changed · +38 lines · +105 tokens per session ef4468573407
- 1mo ago First seen · 41 lines · 74 tokens per session scan A 4a40075ce172
data-analytics is a skill published in the GitHub repository evoelsewhere/evoflux (11 stars, last pushed yesterday), licensed Apache-2.0. It adds 179 tokens to every session and 1,653 once invoked, about $0.0007 per session on Opus 5.5. 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 2026-09-06.
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