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 hamzaPixl/pixl-ai --skill admin-dashboardgit clone --depth 1 https://github.com/hamzaPixl/pixl-aiWrote 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/hamzapixl/pixl-ai/admin-dashboard)<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/admin-dashboard"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/admin-dashboard/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/hamzapixl/pixl-ai/admin-dashboard"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/admin-dashboard.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 | $0.00048 | $0.00436 |
| Opus 5 | $0.00024 | $0.00218 |
| Sonnet 5 | $0.00010 | $0.00087 |
| Haiku 4.5 | $0.00005 | $0.00044 |
Grade A, and why
admin-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 9d 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.
What it actually says
Overview
Builds an admin dashboard with data tables, forms, role-based access control UI, and optional charts/analytics. Uses Next.js with shadcn/ui for the frontend and integrates with a backend API.
Suggested Team
- architect — Data model, page structure, RBAC design
- frontend-engineer — Data tables, forms, dashboard layout
- backend-engineer — API endpoints for CRUD and analytics
- qa-engineer — Testing, accessibility
Process
Phase 1: Discovery
- Identify entities to manage (users, orders, products, etc.)
- Define RBAC roles and what each can see/do
- Determine dashboard metrics and charts needed
- Plan navigation structure (sidebar, breadcrumbs)
Phase 2: Scaffold
- Scaffold from
studio/stacks/nextjs/or existing Next.js project - Install shadcn/ui data table, form, dialog, and chart components
- Create layout with sidebar navigation, header, and main content area
Phase 3: Build
- Build data table pages for each entity (list, filter, sort, paginate)
- Build form pages (create, edit) with Zod validation
- Build detail pages with related data
- Add RBAC-aware navigation (hide/show based on role)
- Add dashboard overview with metrics and charts
Phase 4: Quality
- Run
/self-review-fix-loopfor quality assurance - Run
/agent-browserto verify critical admin flows on the running app - Test with different RBAC roles (admin, member, viewer)
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.
- 9d ago First seen · 48 lines · 48 tokens per session scan A ccacc7cdd940
admin-dashboard is a skill published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 48 tokens to every session and 436 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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