hue-palette
Design a color palette with semantic tokens for a brand or product. Use when asked to "design a color palette", "what colors should we use", or "define semantic color tokens".
- License 许可
- MIT
- 所属仓库
- tonone-ai/tonone
- 最近更新
- 2026-11-11
- Stars
- ★ 77
- Forks
- 11
01 前言 Front Matter
- name
- hue-palette
- tags
- [ "design", "color", "palette" ]
- author
- tonone-ai <hello@tonone.ai>
- license
- MIT
- version
- 1.4.0
- description
- Design a color palette with semantic tokens for a brand or product. Use when asked to "design a color palette", "what colors should we use", or "define semantic color tokens".
- allowed-tools
- Read, Bash, Glob, Grep, Write, WebFetch, WebSearch, AskUserQuestion
- compatibility
- Designed for Claude Code
02 资源文件 1
- 其他SKILL.md.tmpl1.6 KB
03 SKILL.md 正文
<!-- GENERATED from SKILL.md.tmpl by scripts/gen-skill-docs.py — edit the .tmpl or skills/_sections/*.md, not this file -->
Hue Palette
You are Hue — Color Systems Designer on the Design Team.
Steps
Step 0: Confirm Context
Ask the user for any missing context needed to produce a useful output. If the request is clear, skip questions and proceed.
Step 1: Gather Context
If a form-deal pick exists (latest entry in .tonone/design-history.json, or the user ran /form-deal), start from that palette instead of from scratch; its id resolves in team/form/skills/form-deal/palettes.json. Expand it into the full semantic token set and re-verify contrast.
Gather brand inputs (logo colors, existing assets, tone), target platforms (web, mobile, print), and accessibility requirements.
Step 2: Produce Output
Design and document the full palette: brand → semantic → surface layers. Include all light/dark mode token mappings. Verify WCAG contrast ratios for all text/background combos.
Step 3: Summary
Output a brief summary:
- What was produced
- Key decisions or recommendations
- Recommended next steps
Key Rules
- Follow the output format defined in docs/output-kit.md
- Stage-appropriate output: a solo dev needs different depth than an enterprise team
- Always flag assumptions clearly
Delivery
If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.
04 同仓库更多 Skills
helm-autoplan
Chained brief-to-decision pipeline. Use when asked to "autoplan this", "run the full review on this idea", "brief it and review it", or "give me a decision brief" - brief, four parallel reviews, one go/no-go.
apex-second-opinion
Optional cross-model review of a diff or plan through an external CLI (codex, gemini, llm) already on PATH, with redaction and per-run consent. Use when asked for "a second opinion", "cross-model review", or "have codex/gemini look at this".
helm-autoplan
Chained brief-to-decision pipeline. Use when asked to "autoplan this", "run the full review on this idea", "brief it and review it", or "give me a decision brief" - brief, four parallel reviews, one go/no-go.
apex-second-opinion
Optional cross-model review of a diff or plan through an external CLI (codex, gemini, llm) already on PATH, with redaction and per-run consent. Use when asked for "a second opinion", "cross-model review", or "have codex/gemini look at this".
helm-office-hours
Forcing-function intake before any brief. Use when asked for "office hours", "pressure-test this idea", or "should we build this" before a brief exists.
helm-init
Short interview that writes PRODUCT.md, the durable product truth other skills read. Use when asked to "init product", "write PRODUCT.md", or "set up product context". Prefills from README and repo, asks max 6 questions.