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 bestagentkits/agency-skills --skill design-systemgit clone --depth 1 https://github.com/bestagentkits/agency-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/bestagentkits/agency-skills/design-system)<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/design-system"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/design-system/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/bestagentkits/agency-skills/design-system"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/design-system.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 | $0.00204 | $0.02827 |
| Opus 5 | $0.00102 | $0.01413 |
| Sonnet 5 | $0.00041 | $0.00565 |
| Haiku 4.5 | $0.00020 | $0.00283 |
Grade A, and why
design-system 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 8d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design System — Onboarding + Shared Brand Tokens
The design-system skill is the shared brand owner for the markdown-html plugin. Run its onboarding once. Every converter (md-document, md-review, md-slides) reads the resulting config via config_loader.py and applies the same 12 CSS custom properties to its output. Without this, conversions render with placeholder defaults — technically functional but unbranded.
This skill ships exactly three Python tools:
onboard.py— interactive (or--defaults/--set/--show/--reset) wizard.config_loader.py— importable customization loader with project > global > defaults precedence andMARKDOWN_HTML_NO_CONFIG=1bypass.brand_palette_validator.py— WCAG-AA contrast checker + HSL palette deriver.
All three are stdlib-only and contain no LLM calls (deterministic per Path-B discipline).
When to invoke
| Symptom | Action |
|---|---|
| User says "convert this markdown to HTML" for the first time in this workspace | Run python3 markdown-html/skills/design-system/scripts/onboard.py |
~/.config/markdown-html/design-system.json doesn't exist OR setup_completed_at is null |
Refuse conversion, surface onboarding |
| User wants per-repo brand override | python3 .../onboard.py --scope project |
| User wants to change a single field non-interactively | python3 .../onboard.py --set brand.primary=#FF6B35 |
| User wants to reset and re-onboard | python3 .../onboard.py --reset then re-run |
| User wants zero-touch defaults (CI, ephemeral session) | python3 .../onboard.py --defaults |
| Headless / containerized run that should ignore saved config | MARKDOWN_HTML_NO_CONFIG=1 ... |
Onboarding question set (10 questions)
| # | Key | Choices / Validator | Default |
|---|---|---|---|
| 1 | default_output_dir |
path; os.access(parent, os.W_OK) |
./markdown-html-out/ |
| 2 | brand.primary |
HEX ^#?[0-9a-fA-F]{6}$ |
#0A1628 |
| 3 | brand.accent |
HEX or blank (auto-derive) | derive from primary |
| 4 | typography.heading_font |
Google Font name (12 safe defaults) | Inter |
| 5 | typography.body_font |
Google Font name | Inter |
| 6 | design_style |
editorial / technical / minimal / playful |
technical |
| 7 | code_theme |
light / dark / auto |
auto |
| 8 | toc.behavior |
sticky-sidebar / collapsible-top / inline / none |
sticky-sidebar |
| 9 | company_name |
string (may be empty) | "" |
| 10 | logo_url |
URL or empty (base64-embedded at render) | "" |
What ships with it
8 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.yaml 199 B
- assets/design_system_schema.json 4.6 KB
- references/design_token_canon.md 4.2 KB
- references/typography_pairing.md 5.2 KB
- references/wcag_accessibility.md 4.3 KB
- scripts/brand_palette_validator.py 12 KB runs code
- scripts/config_loader.py 4.7 KB runs code
- scripts/onboard.py 9.8 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.
- 8d ago First seen · 163 lines · 204 tokens per session scan A f08198ea71ed
design-system is a skill published in the GitHub repository bestagentkits/agency-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 204 tokens to every session and 2,827 once invoked, about $0.0010 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 2026-09-03.
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