Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jrpease/throughlinenpx agentmods add rules/jrpease/throughline/design-system-auditWrote 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/rules/jrpease/throughline/design-system-audit)<a href="https://agentmods.dev/rules/jrpease/throughline/design-system-audit"><img src="https://agentmods.dev/badge/rules/jrpease/throughline/design-system-audit/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/rules/jrpease/throughline/design-system-audit"><img src="https://agentmods.dev/badge/rules/jrpease/throughline/design-system-audit.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 | $0.00116 | $0.01941 |
| Opus 5.5 | $0.00046 | $0.00776 |
| Sonnet 5.5 | $0.00023 | $0.00388 |
| Haiku 4.5 | $0.00012 | $0.00194 |
Grade A, and why
design-system-audit 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 11d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design-system audit (brownfield front door)
Measures both sides of a pre-existing system so a retrofit can be right-sized,
before anything is built or changed. It is the brownfield analog of
/design-system-status: where status reports a local manifest, this assesses an
external, mature system — a real codebase and an already-populated Figma file.
This is a brownfield skill. Before doing anything, read
.throughline/references/brownfield-retrofit.md — especially the
read-discipline principle (never assert absence without a verified read) and the
audit phase of the safe sequence. Greenfield builds skip this skill entirely.
Calibrate
Read user.codingLevel (.throughline/references/coding-level.md) and scale
explanation accordingly. The audit surfaces grep counts and a percentSemantic
number — for new users explain what each means and why it matters (it decides
rename-vs-rewrite); for comfortable users be terse. The measurements are identical
across levels.
Prerequisites
Read the manifest. This skill needs Figma connected (figma.connected: true) for the
inventory step, and a repo path for the code-surface step (workspace.localPath). If
Figma isn't connected, offer to run figma-environment-setup first. Before the
inventory, do a cheap liveness read to confirm the connection is actually live right
now; if it fails, offer figma-environment-setup. The code-surface
step works on any repo regardless of workspace.stage.
Step 1 — Size the code surface
Measure how many color decisions live in the codebase. Run the color-usage grep scaffold against the user's repo:
node .throughline/scripts/grep-color-usage.mjs --root <workspace.localPath>
It counts five categories: SCSS color vars, Tailwind color classes, Colors.* JS
usages, raw hex + rgba() literals, and SVG hardcoded fills — producing the
case-study worklist shape.
Tune the patterns to the actual repo, and say what you assumed (read discipline + §11). The shipped patterns are defaults, not ground truth. Before trusting the counts:
- Look at the repo's real conventions — open a few SCSS/TS files, check the actual
color-variable prefixes (
$primary-*,$grey-*, a custom prefix), the Tailwind color-class names, and whether colors come through aColors.*object or some other accessor. - If the defaults don't fit, write a
--config <patterns.json>of{ "<category>": { "files": "<regex>", "pattern": "<regex>" } }tuned to this repo and re-run with it. - Report which categories used the assumed defaults vs. a tuned pattern — never present default-pattern counts as if they were measured. The script prints this; pass it through to the user so partial coverage is visible, not hidden.
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.
- 11d ago Changed · +2 lines a051427d8cfe
- 1mo ago First seen · 147 lines · 116 tokens per session scan A 1dc9749b6f7d
design-system-audit is a cursor rule published in the GitHub repository jrpease/throughline (78 stars, last pushed 3d ago), licensed MIT. It adds 116 tokens to every session and 1,941 once invoked, about $0.0005 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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