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/45ck/skill-harness/design-token-alignmentnpx skills add 45ck/skill-harness --skill design-token-alignmentgit clone --depth 1 https://github.com/45ck/skill-harnessWrote 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/45ck/skill-harness/design-token-alignment)<a href="https://agentmods.dev/skills/45ck/skill-harness/design-token-alignment"><img src="https://agentmods.dev/badge/skills/45ck/skill-harness/design-token-alignment.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00242 |
| Opus 5 | $0.00014 | $0.00121 |
| Sonnet 5 | $0.00006 | $0.00048 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
design-token-alignment 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 5d 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
Use this skill when a design needs to map cleanly onto an existing component system or token set.
Checklist:
- identify which design values already map to existing tokens
- flag values that are near-matches and should be normalized instead of copied literally
- note any missing tokens, variant gaps, or component API mismatches
- keep the recommendation biased toward reuse before extension
- produce a concise token and component mapping table
- keep token decisions and component-state mappings in a durable source artifact
- generate a visual review surface when humans need to compare token impact, states, or before/after UI behavior
Good output:
- existing tokens reused where possible
- missing tokens called out explicitly
- API gaps separated from pure styling gaps
- implementation guidance that preserves the current design system shape
- source-backed review path when a generated visual comparison is needed
Avoid:
- creating one-off tokens for every visual exception
- solving a component API problem with raw styling overrides
- assuming the design tool naming is already production-ready
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.
- 5d ago First seen · 31 lines · 28 tokens per session scan A ffb8687de24f
design-token-alignment is a skill published in the GitHub repository 45ck/skill-harness (15 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 242 once invoked, about $0.0001 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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