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/azacdev/knowledge-agent-template/shadcnnpx skills add azacdev/knowledge-agent-template --skill shadcngit clone --depth 1 https://github.com/azacdev/knowledge-agent-templateWhat 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 | $0.00094 | $0.04866 |
| Opus 5 | $0.00047 | $0.02433 |
| Sonnet 5 | $0.00019 | $0.00973 |
| Haiku 4.5 | $0.00009 | $0.00487 |
Grade A, and why
shadcn 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 2d 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.
This is a copy
100% identical to shadcn — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
shadcn/ui
A framework for building ui, components and design systems. Components are added as source code to the user's project via the CLI.
IMPORTANT: Run all CLI commands using the project's package runner:
npx shadcn@latest,pnpm dlx shadcn@latest, orbunx --bun shadcn@latest— based on the project'spackageManager. Examples below usenpx shadcn@latestbut substitute the correct runner for the project.
Current Project Context
!`npx shadcn@latest info --json`
The JSON above contains the project config and installed components. Use npx shadcn@latest docs <component> to get documentation and example URLs for any component.
Principles
- Use existing components first. Use
npx shadcn@latest searchto check registries before writing custom UI. Check community registries too. - Compose, don't reinvent. Settings page = Tabs + Card + form controls. Dashboard = Sidebar + Card + Chart + Table.
- Use built-in variants before custom styles.
variant="outline",size="sm", etc. - Use semantic colors.
bg-primary,text-muted-foreground— never raw values likebg-blue-500.
Critical Rules
These rules are always enforced. Each links to a file with Incorrect/Correct code pairs.
Styling & Tailwind → styling.md
classNamefor layout, not styling. Never override component colors or typography.- No
space-x-*orspace-y-*. Useflexwithgap-*. For vertical stacks,flex flex-col gap-*. - Use
size-*when width and height are equal.size-10notw-10 h-10. - Use
truncateshorthand. Notoverflow-hidden text-ellipsis whitespace-nowrap. - No manual
dark:color overrides. Use semantic tokens (bg-background,text-muted-foreground). - Use
cn()for conditional classes. Don't write manual template literal ternaries. - No manual
z-indexon overlay components. Dialog, Sheet, Popover, etc. handle their own stacking.
Forms & Inputs → forms.md
What ships with it
14 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.
- agents/openai.yml 238 B
- assets/shadcn-small.png 1.0 KB
- assets/shadcn.png 3.8 KB
- cli.md 17 KB
- customization.md 5.9 KB
- evals/evals.json 6.2 KB
- mcp.md 3.4 KB
- registry.md 8.6 KB
- rules/base-vs-radix.md 6.8 KB
- rules/chat.md 6.8 KB
- rules/composition.md 4.8 KB
- rules/forms.md 4.7 KB
- rules/icons.md 1.9 KB
- rules/styling.md 4.6 KB
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.
- 2d ago First seen · 278 lines · 94 tokens per session scan A deba6c5152d9
shadcn is a skill published in the GitHub repository azacdev/knowledge-agent-template (2 stars, last pushed 6d ago), licensed MIT. It adds 94 tokens to every session and 4,866 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to shadcn, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
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chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.