🍷 dsh-palate — an eye that grows
 中文说明 · DeepSeek Harness plugin
> Design-audit tools measure with a fixed ruler. dsh-palate trains an eye that grows.
Most design-review plugins ship a static ruleset and apply it forever — use them once or a thousand times, the judgment is identical. dsh-palate is the opposite: it keeps a taste corpus that accumulates. Every example you feed it and every principle you distill sharpens the judgment your agent draws on. The more you use it, the better its eye gets.
Why this exists
Taste is not a gift — it's pattern recognition built from exposure. See enough good and bad design, and the rules emerge. dsh-palate turns that into a mechanism an agent can actually use:
1. Feed — record designs you judged good or bad, and why 2. Distill — recurring lessons become codified principles 3. Review — critique a new design against the accumulated taste, not a generic checklist 4. Grow — every verdict reinforces the principles it supports; the palate compounds
What the agent gets
| Tool | What it does |
|---|---|
palate_review | Assemble the accumulated taste (principles + relevant past examples) as context, so the agent critiques grounded in learned judgment |
palate_add | Feed an example (good/bad/note + reason + tags) into the corpus — grows the palate |
palate_learn | Distill a new principle from experience and add it to the codified taste |
palate_list | Browse the accumulated corpus |
palate_principles | List the codified principles, ordered by evidence |
palate_stats | How much taste has accumulated: examples studied, principles distilled |
Ships with a starter palate of 12 foundational principles (hierarchy, contrast, type scale, spacing rhythm, alignment, palette discipline, affordance, feedback, clarity, and an anti-AI-slop rule), so it's useful out of the box — then it grows from there.
How it works
palate_add (good/bad + why) ──▶ taste corpus (SQLite + Markdown mirror)
palate_learn (new rule) ──▶ codified principles
palate_review (a design) ──▶ principles + relevant examples ──▶ agent writes grounded critique
▲ │
└──────────────────── verdicts reinforce principles ◀───────────┘- Storage:
node:sqlite(built into Node ≥ 22) at$DSH_HOME/palate/, plus human-readabletaste.md/principles.mdmirrors. Zero runtime dependencies. - The panel: a draggable overlay shows the growth story — examples studied, principles distilled, recent judgments.
- Vision pairing: feed it screenshots by reading them with a vision tool first (e.g.
modlens_read_image), then pass the description topalate_review.
Honest framing
This is accumulated retrieval + codified principles, not model fine-tuning. The plugin supplies the learned taste as context; the model renders the actual critique. That's deliberate: the judgment stays auditable (you can read taste.md and principles.md), and it improves as the corpus grows — without retraining anything.
Install
dsh plugin --profile web add github:guo6x/dsh-palateRequirements: DeepSeek Harness web profile, Node ≥ 22. Restart dsh web, refresh the page — a 👁️ button appears at the sidebar foot.
Develop
pnpm install
node build.mjs # esbuild → lib/index.js (host ESM) + lib/client.js (ModuleLoader bundle)
node tests/smoke.mjs # 17 pure-logic checks (no browser needed)MIT licensed. Ideas and examples welcome — open an issue.
Known limitations
- No semantic matching in the plugin itself — relevance between a subject and past examples is tag/keyword based; the model does the deeper reasoning from the assembled context.
- Markdown mirrors are read-only exports for v0.1 (human edit-and-merge-back is planned).
- Vision is delegated — pair with a vision tool to review screenshots.