Turn subjective quality intent into executable hard gates, weighted rubrics, exemplars, anti-exemplars, blind comparison, and independent judge evidence. Use for high-value artifacts where correctness alone is insufficient.
Scanned 9/3/2026
Install to Claude Code
npx -y skills add frankxai/Starlight-Intelligence-System --skill taste-engine --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: taste-engine
description: Turn subjective quality intent into executable hard gates, weighted rubrics, exemplars, anti-exemplars, blind comparison, and independent judge evidence. Use for high-value artifacts where correctness alone is insufficient.
---
# Taste Engine
## Outcome
Create a domain-specific Taste Profile and an evaluation loop that can reject polished mediocrity without pretending subjective judgment is deterministic.
## Use this skill when
- A high-value artifact must be persuasive, elegant, clear, resonant, or production-ready.
- “Premium,” “beautiful,” “world-class,” or similar intent needs an executable definition.
- Multiple candidates can be compared.
- A winning example should become reusable preference memory.
Do not use a taste rubric as a substitute for factual, security, accessibility, or artifact-native checks.
## Procedure
1. Identify the judgment context.
- Name the artifact type, audience, decision, medium, production constraints, and what failure costs.
2. Write hard rejection gates.
- Encode failures that invalidate an artifact regardless of polish.
- Keep factual fabrication, unusable output, accessibility failure, and broken production constraints outside weighted averaging.
3. Define weighted dimensions.
- Use observable descriptions of excellence and failure.
- Make weights reflect the use case rather than generic aesthetic preference.
- Confirm weights total approximately 1.0.
4. Ground the rubric.
- Add reference exemplars and explain why each wins.
- Add anti-exemplars and name the failure pattern.
- Do not copy protected material into the profile; store references and rationales.
5. Generate candidates only when diversity is useful.
- Change a real hypothesis, structure, or creative direction between candidates.
- Avoid cosmetic variations that create fake choice.
6. Evaluate in layers.
- Run deterministic artifact checks.
- Use blind pairwise comparison where possible.
- Add a domain critic and adversarial reviewer for consequential work.
- Keep the producer from being the sole required judge.
7. Synthesize.
- Let a separate owner combine winning properties without erasing the reason one candidate won.
8. Record preference evidence.
- Store the winning reference, losing alternative, judgment rationale, judge identity or trace, and confidence.
- Mark unrun or non-independent judging as pending.
## Evidence rules
- A judge result counts only when the evidence identifies it as producer-independent.
- Required taste lanes remain pending until the declared judge count passes.
- Taste cannot override a failed hard gate.
- Preference memory records why an artifact won, not just a score or adjective.
## Return
Return the Taste Profile, candidate strategy, deterministic gates, judge plan, Evidence Receipt status, winning rationale, and unresolved disagreement.
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