Install
$ agentstack add skill-dndungu-agent-skills-skin-gallery ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Skin gallery
Concrete pattern: a debug-only screen inside the real app that renders the whole component kit under each candidate skin, so theme decisions are made by LOOKING at real rendering, never by reading hex tables. Child pattern of /design-fidelity-loop step 3.
1. What the gallery renders
- Every shared kit component (buttons, cards, chips, rows, sheet header,
progress, empty state, badges...) in one scrollable screen — real components from the kit, not mockups.
- Grouped per candidate skin, side by side, so the reviewer compares like
against like in one glance.
- Intensity/variant tiers (e.g. material intensity, wash strength, accent
level) rendered side-by-side as labeled rows — the reviewer POINTS at a tier instead of describing a feeling.
- Material/glass components must sit over RICH backdrop content (gradient,
imagery, scrolling content) — over a flat fill, translucency reads as gray and the comparison is meaningless. Remember blur desaturates: washes need real chroma to survive.
2. Reachable by launch seam
- Behind a debug flag / launch argument (never shipped in Release; keep it
inside the debug conditional and verify with a Release build).
- Directly launchable so automated capture can drive it: launch app with
the seam arg, land on the gallery, screenshot, exit.
3. Evidence discipline
- Capture LIGHT AND DARK per skin, on a fresh simulator/clean environment.
- Contrast-audit every fg/bg slot pair (WCAG ratios) BEFORE capture — do
not spend a founder review round discovering unreadable text a script could have caught. Known trap: dark-mode primary CTA label color.
- Version evidence files by iteration prefix (e.g.
r3-ember-dark.png) so
the feedback thread can reference exact shots and rounds never overwrite each other.
4. The feedback loop
- Capture the gallery set; post shots to the reviewer.
- Reviewer reacts to specific shots/tiers ("r3 ember, tier 2, but warmer
glow").
- Translate the reaction into concrete SLOT/tier changes (skins are slot
remaps — one file, app-wide effect).
- Recapture with the next iteration prefix. Repeat until approved.
- The decision belongs to the reviewer's eyes on rendered pixels, not to
anyone's judgment of a palette table.
5. Pairing with a multi-model design council
- For divergent palette directions, run the /council skill on the design
brief — then RENDER the council's candidate directions as actual gallery skins (typically the top 2 opposing camps, e.g. one warm, one cool) and judge them in the gallery, not as hex tables.
- Carry unanimous council keeps (settled slots/rules) into every candidate;
render only the disputed axes.
6. After approval
- The winning skin's slots land in the token file; the gallery stays in the
tree as the permanent regression surface for future skin work.
- Record the approved decision + evidence paths in the project's design
skill / lore so later lanes don't relitigate it.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: dndungu
- Source: dndungu/agent-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.