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 ancoleman/ai-design-components --skill assembling-componentsgit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote 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/ancoleman/ai-design-components/assembling-components)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/assembling-components"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/assembling-components/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/ancoleman/ai-design-components/assembling-components"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/assembling-components.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 | $0.00074 | $0.03217 |
| Opus 5.5 | $0.00030 | $0.01287 |
| Sonnet 5.5 | $0.00015 | $0.00643 |
| Haiku 4.5 | $0.00007 | $0.00322 |
Grade A, and why
assembling-components 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 — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assembling Components
Purpose
This skill transforms the outputs of AI Design Components skills into production-ready applications. It provides library-specific context for our token system, component patterns, and skill chain workflow - knowledge that generic assembly patterns cannot provide. The skill validates token integration, generates proper scaffolding, and wires components together correctly.
When to Use
Activate this skill when:
- Completing a skill chain workflow (theming → layout → dashboards → data-viz → feedback)
- Generating new project scaffolding for React/Vite, Next.js, FastAPI, Flask, or Rust/Axum
- Validating that all generated CSS uses design tokens (not hardcoded values)
- Creating barrel exports and wiring component imports correctly
- Assembling components from multiple skills into a unified application
- Debugging integration issues (missing entry points, broken imports, theme not switching)
- Preparing generated code for production deployment
Skill Chain Context
This skill understands the output of every AI Design Components skill:
┌──────────────────┐ ┌──────────────────┐ ┌──────────────────┐
│ theming- │────▶│ designing- │────▶│ creating- │
│ components │ │ layouts │ │ dashboards │
└──────────────────┘ └──────────────────┘ └──────────────────┘
│ │ │
▼ ▼ ▼
tokens.css Layout.tsx Dashboard.tsx
theme-provider.tsx Header.tsx KPICard.tsx
│ │ │
└────────────────────────┴────────────────────────┘
│
▼
┌──────────────────────┐
│ visualizing-data │
│ providing-feedback │
└──────────────────────┘
│
▼
DonutChart.tsx
Toast.tsx, Spinner.tsx
│
▼
┌──────────────────────┐
│ ASSEMBLING- │
│ COMPONENTS │
│ (THIS SKILL) │
└──────────────────────┘
│
▼
WORKING COMPONENT SYSTEM
What ships with it
19 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.
- assets/templates/python/README.md 1.7 KB
- assets/templates/react/README.md 2.0 KB
- assets/templates/rust/README.md 2.1 KB
- examples/fastapi-dashboard/README.md 1.7 KB
- examples/nextjs-dashboard/README.md 2.7 KB
- examples/react-dashboard/README.md 2.2 KB
- examples/README.md 2.5 KB
- examples/rust-axum-dashboard/README.md 1.7 KB
- outputs.yaml 10 KB
- references/library-context.md 14 KB
- references/nextjs-template.md 9.3 KB
- references/python-fastapi-template.md 11 KB
- references/react-vite-template.md 8.7 KB
- references/rust-axum-template.md 10 KB
- references/token-validation-rules.md 8.8 KB
- scripts/check_imports.py 14 KB runs code
- scripts/generate_exports.py 7.5 KB runs code
- scripts/generate_scaffold.py 22 KB runs code
- scripts/validate_tokens.py 17 KB runs code
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 · 433 lines · 74 tokens per session scan A e492701d3fa1
assembling-components is a skill published in the GitHub repository ancoleman/ai-design-components (525 stars, last pushed 10mo ago), licensed MIT. It adds 74 tokens to every session and 3,217 once invoked, about $0.0003 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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