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 joao-aires/agent-skills-public --skill saas-dashboard-designgit clone --depth 1 https://github.com/joao-aires/agent-skills-publicWrote 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/joao-aires/agent-skills-public/saas-dashboard-design)<a href="https://agentmods.dev/skills/joao-aires/agent-skills-public/saas-dashboard-design"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/saas-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/joao-aires/agent-skills-public/saas-dashboard-design"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/saas-dashboard-design.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 | $0.00042 | $0.00762 |
| Opus 5.5 | $0.00017 | $0.00305 |
| Sonnet 5.5 | $0.00008 | $0.00152 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
saas-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 yesterday.
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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design dashboards for decisions and work
Identify the audience, their recurring tasks, the decisions this surface should support and the cost of acting on the wrong context. Separate customer workspaces, customer administration and internal operator tools. Reuse sufficient product evidence and accepted visual direction; a dashboard request does not automatically reopen branding or select a UI library. Read dashboard decisions for data/interaction tradeoffs and the source review for inspected open-source examples.
Establish context and hierarchy
Begin with the work this audience returns to do. Determine what needs attention, what information explains the situation, and which action follows. Use that relationship to choose the starting view and navigation. An overview is useful when it helps prioritize work; a task list or detailed workspace may be the better starting point when users already know what they need to do.
Make organization/workspace, time range, environment and relevant resource scope recognizable before consequential actions. Preserve that context through drill-downs and return navigation so a user can investigate a record without rebuilding their filters or losing their place.
Give each summary or metric a decision it supports. Establish what a change in the value would lead the user to do, then choose the surrounding explanation and route to detail. Compare layouts using realistic data distributions, including long names, large counts and uneven activity, rather than arranging identical cards around invented metrics.
Derive hierarchy, typography, density, color and interaction language from the product's purpose and accepted design system. Seek available interface craft, interaction, accessibility and writing expertise by capability. When absent, make and inspect a coherent direction with project evidence and appropriate references. Use the accepted stack's components/tokens; the skill does not require a framework, design tool or chart library.
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.
- yesterday First seen · 59 lines · 42 tokens per session scan A c95f59304462
saas-dashboard-design is a skill published in the GitHub repository joao-aires/agent-skills-public (2 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 762 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 2026-10-21.
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