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 DeepSQLAI/deepsql --skill dashboard-designgit clone --depth 1 https://github.com/DeepSQLAI/deepsqlWrote 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/deepsqlai/deepsql/dashboard-design)<a href="https://agentmods.dev/skills/deepsqlai/deepsql/dashboard-design"><img src="https://agentmods.dev/badge/skills/deepsqlai/deepsql/dashboard-design/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/deepsqlai/deepsql/dashboard-design"><img src="https://agentmods.dev/badge/skills/deepsqlai/deepsql/dashboard-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 30 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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 | $0.00043 | $0.05273 |
| Opus 5.5 | $0.00017 | $0.02109 |
| Sonnet 5.5 | $0.00009 | $0.01055 |
| Haiku 4.5 | $0.00004 | $0.00527 |
Grade A, and why
dashboard-design 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 1mo 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 — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dashboard Design
Use when asked to build or edit a dashboard (the task says "build a self-contained HTML dashboard"). You are a coding agent building a small, beautiful BI web app that renders inside DeepSQL — not filling in a rigid template.
The runtime you build against
Your output is a shell block, then one widget block per KPI/chart — not a single HTML
document. The parent assembles them (each widget's markup+script drops into its own
[data-widget=id] slot in the shell) and renders each widget into the live canvas the moment
its block closes, well before your whole turn finishes — so the user watches the dashboard
build piece by piece instead of staring at a blank screen for the whole generation. Both kinds
of block run inside the SAME sandboxed iframe with a bridge already injected:
deepsql.connectionId // this connection's id (string)
await deepsql.query("SELECT ...") // -> { columns: string[], rows: any[][] } (read-only, access-scoped)
deepsql.ready(fn) // runs fn() once the bridge is live (use this to kick off loading)
// Charts — ALWAYS use these instead of hand-writing SVG. Built-in hover tooltips
// (show the value on mouse-over), number formatting, sparse axis labels, a
// graceful "No data" empty state, and a corner expand button that opens the
// same chart larger in an overlay — all automatic, nothing to wire yourself.
// Pass the deepsql.query result straight in, or [{label,value}] / [[label,value]].
// First column = label, second = value (or opts.labelKey/valueKey).
// opts: { valueFormat(fn), height, color, emptyText, title }.
deepsql.charts.bar(elOrSelector, data, opts) // rankings, counts by day
deepsql.charts.line(elOrSelector, data, opts) // trends over time (area+line)
deepsql.charts.donut(elOrSelector, data, opts) // share/composition (with legend + %)
deepsql.charts.format(n) // human number formatter
Chart sizing and the expand control are handled by the runtime — do not build your own.
Height is fixed regardless of container width (a chart in a wide card never balloons), and every
chart already gets a corner "expand" button that opens a larger re-render in an overlay — this is
exactly the kind of per-chart chrome that's tempting to hand-roll and easy to get inconsistent
across widgets, so it's built into deepsql.charts.* once instead. Pass opts.title (the chart's
plain-business-language heading) so the expanded overlay has something to show as its title — do
not add your own zoom/expand/fullscreen button, modal, or lightbox; one already exists per chart.
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.
- 1mo ago First seen · 294 lines · 43 tokens per session scan A f26453d243a3
dashboard-design is a skill published in the GitHub repository DeepSQLAI/deepsql (39 stars, last pushed 5d ago), licensed Apache-2.0. It adds 43 tokens to every session and 5,273 once invoked, about $0.0002 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 2026-08-30.
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