Ghost is a publishing platform for creating websites, blogs, memberships, subscriptions, and newsletters. Publishers and developers can use it through managed hosting or run it themselves, while contributors work on its monorepo, themes, and API.
Borrowing it
Nothing to install: this file belongs to TryGhost/Ghost. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TryGhost/Ghost/main/.agents/skills/shade-dropdown-surface-contract/SKILL.mdgit clone --depth 1 https://github.com/TryGhost/GhostWrote 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/tryghost/ghost/shade-dropdown-surface-contract)<a href="https://agentmods.dev/skills/tryghost/ghost/shade-dropdown-surface-contract"><img src="https://agentmods.dev/badge/skills/tryghost/ghost/shade-dropdown-surface-contract/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/tryghost/ghost/shade-dropdown-surface-contract"><img src="https://agentmods.dev/badge/skills/tryghost/ghost/shade-dropdown-surface-contract.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 28 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 30 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 31 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 33 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 34 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00054 | $0.00968 |
| Opus 5.5 | $0.00022 | $0.00387 |
| Sonnet 5.5 | $0.00011 | $0.00194 |
| Haiku 4.5 | $0.00005 | $0.00097 |
Grade A, and why
Shade dropdown surface contract 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 2d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shade — dropdown surface contract
DropdownMenu, Select, and Popover are the three Radix-backed floating menus that Filters and the rest of admin use. They share one visual recipe:
bg-surface-elevated-2
border border-border/60 dark:border-border/30
shadow-md
Treat them as one component for any surface decision. If you change the surface for one, change all three.
Why this exists
Floating menus open ON TOP of an already-elevated surface (sidebars, cards, top bars). They need to read as floating above their trigger. --surface-elevated-2 is reserved for exactly this — popovers, dropdown content, and the sidebar user menu.
In light mode the three surface tokens (background / surface-elevated / surface-elevated-2) flatten to near-white; the border + shadow-md carry elevation. In dark mode they're three distinct colours so layered surfaces stay legible without relying on borders alone.
The contract
| Concern | Class |
|---|---|
| Background | bg-surface-elevated-2 |
| Border | border border-border/60 dark:border-border/30 |
| Shadow | shadow-md baseline. DropdownMenuSubContent is the exception — it uses shadow-lg. DropdownMenuContent, SelectContent, and PopoverContent all use shadow-md. |
| Radius | rounded-md (component default) |
| Animation | Standard Radix data-[state=open]: enter/exit set |
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.
- 2d ago Changed a1a9a541cbf9
- 2mo ago First seen · 77 lines · 54 tokens per session scan A 3c24cf33f7dc
Shade dropdown surface contract is a skill published in the GitHub repository TryGhost/Ghost (55,632 stars, last pushed today), licensed MIT. It adds 54 tokens to every session and 968 once invoked, about $0.0002 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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Guides exploration of $autocapture events captured by posthog-js to understand user interactions, find CSS selectors (especially data-attr attributes), evaluate selector uniqueness, query matching clicks ad-hoc, and create actions. Use when the user asks about autocapture data, wants to find what users are clicking…