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 agentmods add skills/minhlucvan/notebookmd/dashboardnpx skills add minhlucvan/notebookmd --skill dashboardgit clone --depth 1 https://github.com/minhlucvan/notebookmdWhat 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 | $0.00037 | $0.00807 |
| Opus 5 | $0.00018 | $0.00404 |
| Sonnet 5 | $0.00007 | $0.00161 |
| Haiku 4.5 | $0.00004 | $0.00081 |
Grade A, and why
dashboard 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 3d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Metrics Dashboard Generator
Generate a KPI dashboard as a structured Markdown report using notebookmd.
Input
Dashboard: $ARGUMENTS
Instructions
1. Setup
from notebookmd import nb, NotebookConfig
cfg = NotebookConfig(max_table_rows=20)
n = nb("dist/dashboard.md", title="<Dashboard Title>", cfg=cfg)
2. Dashboard Layout
# Hero Metrics Row
n.section("Key Performance Indicators")
n.metric_row([
{"label": "Revenue", "value": "$4.2M", "delta": "+18%"},
{"label": "Users", "value": "34.5K", "delta": "+2,100"},
{"label": "Conversion", "value": "3.2%", "delta": "+0.4%"},
{"label": "Churn", "value": "1.8%", "delta": "-0.3%", "delta_color": "inverse"},
])
# Status Badges
n.badge("ON TRACK", style="success")
n.badge("Q4 2026", style="info")
# Trend Charts
n.section("Trends")
n.line_chart(df, x="date", y="revenue", title="Revenue Trend")
n.area_chart(df, x="date", y="users", title="User Growth")
n.bar_chart(df, x="category", y="count", title="Distribution")
# Detailed Metrics
n.section("Detailed Metrics")
n.kv({
"MRR": "$350K",
"ARR": "$4.2M",
"LTV": "$1,200",
"CAC": "$180",
"LTV/CAC": "6.7x",
}, title="Unit Economics")
# Period Comparison
n.section("Period Comparison")
n.change("Revenue", current=4_200_000, previous=3_560_000, fmt=",.0f", pct=True)
n.change("Users", current=34_521, previous=32_421, fmt=",d", pct=True)
n.change("Churn", current=0.018, previous=0.021, fmt=".1%", pct=True)
# Rankings
n.section("Top Performers")
n.ranking("Product A", value="$1.2M", rank=1, total=15)
n.ranking("Product B", value="$890K", rank=2, total=15)
n.ranking("Product C", value="$650K", rank=3, total=15)
# Data Tables
n.section("Data Tables")
n.dataframe(summary_df, name="Summary by Segment")
# Alerts
n.section("Alerts & Actions")
n.success("Revenue target exceeded by 12%")
n.warning("Churn rate increasing in Enterprise segment")
n.info("New pricing tier launching next quarter")
# Export
n.export_csv(df, "dashboard_data.csv", name="Dashboard data export")
n.save()
What ships with it
1 file 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.
- 3d ago First seen · 96 lines · 37 tokens per session scan A 0b05b2453d44
dashboard is a skill published in the GitHub repository minhlucvan/notebookmd (10 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 807 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 2026-08-31.
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