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 donvito/skillsbento --skill product-sales-analysisgit clone --depth 1 https://github.com/donvito/skillsbentoWrote 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/donvito/skillsbento/product-sales-analysis)<a href="https://agentmods.dev/skills/donvito/skillsbento/product-sales-analysis"><img src="https://agentmods.dev/badge/skills/donvito/skillsbento/product-sales-analysis/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/donvito/skillsbento/product-sales-analysis"><img src="https://agentmods.dev/badge/skills/donvito/skillsbento/product-sales-analysis.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 | $0.00080 | $0.01667 |
| Opus 5 | $0.00040 | $0.00834 |
| Sonnet 5 | $0.00016 | $0.00333 |
| Haiku 4.5 | $0.00008 | $0.00167 |
Grade A, and why
product-sales-analysis 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 11d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Sales Analysis Skill
Analyze sales data to extract actionable business insights and generate interactive HTML dashboards using pure CSS (no frameworks).
Expected Data Format
CSV with columns like:
Date— Daily/weekly/monthly dateProduct_Category— Category nameUnits_Sold/Quantity— Volume soldRevenue/Sales/Price×Units— Revenue figuresProfit/Margin(optional) — ProfitabilityMarketing_Spend(optional) — Marketing costsCustomer_Segment/Region(optional) — Dimensions
Analysis Workflow
Step 1: Load & Explore Data
import pandas as pd
df = pd.read_csv('sales_data.csv')
df['Date'] = pd.to_datetime(df['Date'])
df['Year'] = df['Date'].dt.year
df['Month'] = df['Date'].dt.month
df['Quarter'] = df['Date'].dt.quarter
Step 2: Compute Core Metrics
By Category: Total Revenue, Units Sold, Revenue Share (%), Marketing ROI
Time-Based: Monthly/Quarterly trends, YoY growth: ((Y2 - Y1) / Y1) * 100
By Segment: Revenue by customer segment, Average order value
Step 3: Identify Insights
| Pattern | Insight Type | Action |
|---|---|---|
| YoY Growth > 20% | 🟢 Success | Invest more, expand |
| YoY Growth < -10% | 🔴 Decline | Reassess, reduce spend |
| Marketing ROI < avg | 🟡 Warning | Optimize or cut |
| Q4 < 25% of annual | 🟡 Seasonal gap | Holiday strategy needed |
Step 4: Generate Dashboard
Output single HTML file. See assets/dashboard_template.html for complete structure.
Dashboard HTML Structure
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Dashboard</title>
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<style>
/* Include full CSS from template */
</style>
</head>
<body>
<div class="container"><!-- Components --></div>
<script>/* Charts */</script>
</body>
</html>
CSS Classes Reference
What ships with it
2 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.
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.
- 11d ago First seen · 189 lines · 80 tokens per session scan A 1acfae38e2e4
product-sales-analysis is a skill published in the GitHub repository donvito/skillsbento (2 stars, last pushed 28d ago), licensed Apache-2.0. It adds 80 tokens to every session and 1,667 once invoked, about $0.0004 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 2026-08-31.
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