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+---
+name: negative-contrastive-framing
+description: Use when clarifying fuzzy boundaries, defining quality criteria, teaching by counterexample, preventing common mistakes, setting design guardrails, disambiguating similar concepts, refining requirements through anti-patterns, creating clear decision criteria, or when user mentions near-miss examples, anti-goals, what not to do, negative examples, counterexamples, or boundary clarification.
+---
+
+# Negative Contrastive Framing
+
+## Table of Contents
+- [Purpose](#purpose)
+- [When to Use](#when-to-use)
+- [What Is It](#what-is-it)
+- [Workflow](#workflow)
+- [Common Patterns](#common-patterns)
+- [Guardrails](#guardrails)
+- [Quick Reference](#quick-reference)
+
+## Purpose
+
+Define concepts, quality criteria, and boundaries by showing what they're NOT—using anti-goals, near-miss examples, and failure patterns to create crisp decision criteria where positive definitions alone are ambiguous.
+
+## When to Use
+
+**Clarifying Fuzzy Boundaries:**
+- Positive definition exists but edges are unclear
+- Multiple interpretations cause confusion
+- Team debates what "counts" as meeting criteria
+- Need to distinguish similar concepts
+
+**Teaching & Communication:**
+- Explaining concepts to learners who need counterexamples
+- Training teams to recognize anti-patterns
+- Creating style guides with do's and don'ts
+- Onboarding with common mistake prevention
+
+**Setting Standards:**
+- Defining code quality (show bad patterns)
+- Establishing design principles (show violations)
+- Creating evaluation rubrics (clarify failure modes)
+- Building decision criteria (identify disqualifiers)
+
+**Preventing Errors:**
+- Near-miss incidents revealing risk patterns
+- Common mistakes that need explicit guards
+- Edge cases that almost pass but shouldn't
+- Subtle failures that look like successes
+
+## What Is It
+
+Negative contrastive framing defines something by showing what it's NOT:
+
+**Types of Negative Examples:**
+1. **Anti-goals:** Opposite of desired outcome ("not slow" → define fast)
+2. **Near-misses:** Examples that almost qualify but fail on key dimension
+3. **Failure patterns:** Common mistakes that violate criteria
+4. **Boundary cases:** Edge examples clarifying where line is drawn
+
+**Example:**
+Defining "good UX":
+- **Positive:** "Intuitive, efficient, delightful"
+- **Negative contrast:**
+  - ❌ Near-miss: Fast but confusing (speed without clarity)
+  - ❌ Anti-pattern: Dark patterns (manipulative design)
+  - ❌ Failure: Requires manual to understand basic tasks
+
+## Workflow
+
+Copy this checklist and track your progress:
+
+```
+Negative Contrastive Framing Progress:
+- [ ] Step 1: Define positive concept
+- [ ] Step 2: Identify negative examples
+- [ ] Step 3: Analyze contrasts
+- [ ] Step 4: Validate quality
+- [ ] Step 5: Deliver framework
+```
+
+**Step 1: Define positive concept**
+
+Start with initial positive definition, identify why it's ambiguous or fuzzy (multiple interpretations, edge cases unclear), and clarify purpose (teaching, decision-making, quality control). See [Common Patterns](#common-patterns) for typical applications.
+
+**Step 2: Identify negative examples**
+
+For simple cases with clear anti-patterns → Use [resources/template.md](resources/template.md) to structure anti-goals, near-misses, and failure patterns. For complex cases with subtle boundaries → Study [resources/methodology.md](resources/methodology.md) for techniques like contrast matrices and boundary mapping.
+
+**Step 3: Analyze contrasts**
+
+Create `negative-contrastive-framing.md` with: positive definition, 3-5 anti-goals, 5-10 near-miss examples with explanations, common failure patterns, clear decision criteria ("passes if..." / "fails if..."), and boundary cases. Ensure contrasts reveal the *why* behind criteria.
+
+**Step 4: Validate quality**
+
+Self-assess using [resources/evaluators/rubric_negative_contrastive_framing.json](resources/evaluators/rubric_negative_contrastive_framing.json). Check: negative examples span the boundary space, near-misses are genuinely close calls, contrasts clarify criteria better than positive definition alone, failure patterns are actionable guards. Minimum standard: Average score ≥ 3.5.
+
+**Step 5: Deliver framework**
+
+Present completed framework with positive definition sharpened by negatives, most instructive near-misses highlighted, decision criteria operationalized as checklist, common mistakes identified for prevention.
+
+## Common Patterns
+
+### By Domain
+
+**Engineering (Code Quality):**
+- Positive: "Maintainable code"
+- Negative: God objects, tight coupling, unclear names, magic numbers, exception swallowing
+- Near-miss: Well-commented spaghetti code (documentation without structure)
+
+**Design (UX):**
+- Positive: "Intuitive interface"
+- Negative: Hidden actions, inconsistent patterns, cryptic error messages
+- Near-miss: Beautiful but unusable (form over function)
+
+**Communication (Clear Writing):**
+- Positive: "Clear documentation"
+- Negative: Jargon-heavy, assuming context, no examples, passive voice
+- Near-miss: Technically accurate but incomprehensible to target audience
+
+**Strategy (Market Positioning):**
+- Positive: "Premium brand"
+- Negative: Overpriced without differentiation, luxury signaling without substance
+- Near-miss: High price without service quality to match
+
+### By Application
+
+**Teaching:**
+- Show common mistakes students make
+- Provide near-miss solutions revealing misconceptions
+- Identify "looks right but is wrong" patterns
+
+**Decision Criteria:**
+- Define disqualifiers (automatic rejection criteria)
+- Show edge cases that almost pass
+- Clarify ambiguous middle ground
+
+**Quality Control:**
+- Identify anti-patterns to avoid
+- Show subtle defects that might pass inspection
+- Define clear pass/fail boundaries
+
+## Guardrails
+
+**Near-Miss Selection:**
+- Near-misses must be genuinely close to positive examples
+- Should reveal specific dimension that fails (not globally bad)
+- Avoid trivial failures—focus on subtle distinctions
+
+**Contrast Quality:**
+- Explain *why* each negative example fails
+- Show what dimension violates criteria
+- Make contrasts instructive, not just lists
+
+**Completeness:**
+- Cover failure modes across key dimensions
+- Don't cherry-pick—include hard-to-classify cases
+- Show spectrum from clear pass to clear fail
+
+**Actionability:**
+- Translate insights into decision rules
+- Provide guards/checks to prevent failures
+- Make criteria operationally testable
+
+**Avoid:**
+- Strawman negatives (unrealistically bad examples)
+- Negatives without explanation (show what's wrong and why)
+- Missing the "close call" zone (all examples clearly pass or fail)
+
+## Quick Reference
+
+**Resources:**
+- `resources/template.md` - Structured format for anti-goals, near-misses, failure patterns
+- `resources/methodology.md` - Advanced techniques (contrast matrices, boundary mapping, failure taxonomies)
+- `resources/evaluators/rubric_negative_contrastive_framing.json` - Quality criteria
+
+**Output:** `negative-contrastive-framing.md` with positive definition, anti-goals, near-misses with analysis, failure patterns, decision criteria
+
+**Success Criteria:**
+- Negative examples span boundary space (not just extremes)
+- Near-misses are instructive close calls
+- Contrasts clarify ambiguous criteria
+- Failure patterns are actionable guards
+- Decision criteria operationalized
+- Score ≥ 3.5 on rubric
+
+**Quick Decisions:**
+- **Clear anti-patterns?** → Template only
+- **Subtle boundaries?** → Use methodology for contrast matrices
+- **Teaching application?** → Emphasize near-misses revealing misconceptions
+- **Quality control?** → Focus on failure pattern taxonomy
+
+**Common Mistakes:**
+1. Only showing extreme negatives (not instructive near-misses)
+2. Lists without analysis (not explaining why examples fail)
+3. Cherry-picking easy cases (avoiding hard boundary calls)
+4. Strawman negatives (unrealistically bad)
+5. No operationalization (criteria remain fuzzy despite contrasts)
+
+**Key Insight:**
+Negative examples are most valuable when they're *almost* positive—close calls that force articulation of subtle criteria invisible in positive definition alone.