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 thedesignproject/agent-skills --skill agentic-design-systemsgit clone --depth 1 https://github.com/thedesignproject/agent-skillsWrote 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/thedesignproject/agent-skills/agentic-design-systems)<a href="https://agentmods.dev/skills/thedesignproject/agent-skills/agentic-design-systems"><img src="https://agentmods.dev/badge/skills/thedesignproject/agent-skills/agentic-design-systems/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/thedesignproject/agent-skills/agentic-design-systems"><img src="https://agentmods.dev/badge/skills/thedesignproject/agent-skills/agentic-design-systems.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00136 | $0.02528 |
| Opus 5 | $0.00068 | $0.01264 |
| Sonnet 5 | $0.00027 | $0.00506 |
| Haiku 4.5 | $0.00014 | $0.00253 |
Grade A, and why
agentic-design-systems 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.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Design Systems
When this skill triggers, you're helping the user build, extend, or audit a component library whose primary consumer is an AI agent. The bar: given a prose request like "Build a confirmation modal with a destructive action," an agent picks the right component, the right variant, and the right tokens — without inventing patterns.
This skill gives you the schema, the workflow, and the principles. Adapt it to where the user is.
Diagnose first
Before producing anything, figure out which mode applies:
- Greenfield — user is starting a new system intended for agent consumption. Walk through the build workflow. Start with the schema and one worked component (Button is canonical); don't try to scaffold everything at once.
- Retrofitting — user has a component library and wants to make it agent-readable. Skip workspace setup. Add
meta.types.ts, then write a.meta.tsper component, then build the index and validator. Anti-patterns first (see Step 5). - Auditing — user has metadata already. Score each component against the four pillars and the validator checks. Flag missing relationships, prose anti-patterns, raw global tokens, and ungrounded variant axes.
- Single component — user wants to add or fix one component. Generate the full file set in Step 3. Metadata ships with the component or it doesn't ship.
If the prompt is ambiguous, ask one targeted question — don't guess.
The four pillars
Treat every component as the intersection of four things. Most metadata schemas only model the first; that's why agents misuse the components.
| Pillar | What it answers | Failure mode if missing |
|---|---|---|
| Props | What you set | (always present) |
| Variants | Which combination to pick | Agent picks invalid combinations |
| Relationships | Where the component fits structurally and a11y-wise | Agent generates code that compiles but is structurally wrong |
| Tokens (component-scoped) | Which design values bind to this component | Agent invents colors and spacing |
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 · 208 lines · 136 tokens per session scan A 2658d07d93a7
agentic-design-systems is a skill published in the GitHub repository thedesignproject/agent-skills (86 stars, last pushed 14d ago), licensed MIT. It adds 136 tokens to every session and 2,528 once invoked, about $0.0007 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 2026-08-30.
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