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gh-yaleh-meta-cc-claude/skills/baseline-quality-assessment/reference/quality-levels.md
2025-11-30 09:07:22 +08:00

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# Baseline Quality Levels
**V_meta(s₀) thresholds and expected outcomes**
---
## Level 1: Excellent (0.60-1.0)
**Characteristics**:
- Comprehensive data analysis (ALL available data)
- 70-80% initial coverage
- Significant prior art borrowed (≥60%)
- All automation identified upfront
**Investment**: 6-10 hours
**Outcome**: 3-4 iterations (rapid convergence)
**Examples**: Bootstrap-003 (V_meta=0.758)
---
## Level 2: Good (0.40-0.59)
**Characteristics**:
- Thorough analysis (≥80% of data)
- 50-70% initial coverage
- Moderate borrowing (30-60%)
- Top 3 automations identified
**Investment**: 4-6 hours
**Outcome**: 4-5 iterations
**ROI**: 2-3x (saves 8-12 hours overall)
---
## Level 3: Fair (0.20-0.39)
**Characteristics**:
- Partial analysis (50-80% of data)
- 30-50% initial coverage
- Limited borrowing (<30%)
- 1-2 automations identified
**Investment**: 2-4 hours
**Outcome**: 5-7 iterations (standard)
---
## Level 4: Poor (<0.20)
**Characteristics**:
- Minimal analysis (<50% of data)
- <30% coverage
- Little/no prior art research
- Unclear automation
**Investment**: <2 hours
**Outcome**: 7-10 iterations (exploratory)
---
**Recommendation**: Target Level 2 (≥0.40) minimum for quality convergence.