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.
git clone --depth 1 https://github.com/perniemann/pnCoreWrote 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/perniemann/pncore/pn-figma)<a href="https://agentmods.dev/rules/perniemann/pncore/pn-figma"><img src="https://agentmods.dev/badge/rules/perniemann/pncore/pn-figma/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/perniemann/pncore/pn-figma"><img src="https://agentmods.dev/badge/rules/perniemann/pncore/pn-figma.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 | $0.00230 | $0.00230 |
| Opus 5.5 | $0.00092 | $0.00092 |
| Sonnet 5.5 | $0.00046 | $0.00046 |
| Haiku 4.5 | $0.00023 | $0.00023 |
Grade A, and why
pn-figma 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.
What it actually says
Figma rules
- Extract design tokens (colors, spacing, typography) from Figma before implementing; use tokens in code, not raw values from the design.
- Map Figma components/frames to React/Astro components with consistent naming; sanitize layer names (PascalCase for components, kebab-case for CSS).
- Use Figma auto-layout semantics when implementing: flex/grid with gap for spacing; preserve direction and alignment.
- Document intentional deviations from design; when specs are ambiguous, use design-system conventions and note assumptions.
- Keep token definitions in sync with Figma styles when design is the source of truth; update tokens before components when designs change.
- Use Figma MCP when available for direct token extraction and component inspection; fall back to manual export when MCP is unavailable.
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 · 15 lines · 230 tokens per session scan A 8a9a0b2d06c8
pn-figma is a cursor rule published in the GitHub repository perniemann/pnCore (0 stars, last pushed 2d ago), licensed MIT. It adds 230 tokens to every session, about $0.0009 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 2026-08-31.
Other cursor rules, from other repositories
visual-style
Visual Style, glyph renders in chat. Reset 2026-09-17 by operator word after seeing a peer's disk-cleanup render.
best_practices
Advanced Best Practices covering Error Handling, Environment Variables, Performance, and Accessibility rules.
t-800-mandatory-routing
A mandatory routing rule for creating or changing subagents, skills, commands, rules, and hooks. Hooks are scripts that run automatically when certain events occur.
t-800-operator-routing
A routing rule for explaining Cursor and its agent features to Russian-speaking beginners. Cursor is a code editor with built-in AI assistance.
t-800-factory-routing
A routing rule for building and coordinating groups of coding subagents. Subagents are separate agents that handle parts of a larger task.
t-800-cloud-hub-routing
A routing rule for Cloud Hub setup work, sending matching requests to a designated lead agent. Cloud Hub is the project area named in the rule.