Files
gh-rpiplewar-shipfaster-con…/commands/content-score-all.md
2025-11-30 08:52:57 +08:00

137 lines
4.0 KiB
Markdown
Raw Permalink Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
---
description: "Apply automated 3-framework scoring to all content variations"
---
# Score All Content Variations
## Mission
Apply automated framework-based scoring (Gap Selling + Munger Biases + Decision Framework) to all content variations in content-drafts.md, calculating total scores with detailed breakdowns.
## Process
Follow the Scorer agent instructions (`agents/scorer.md`) to:
1. **Read all content variations** from content-drafts.md
2. **Apply 3-framework scoring** with mathematical formulas
3. **Calculate total scores** (out of 30)
4. **Update content-drafts.md** with complete score breakdowns
## Execution Steps
### Step 1: Read Content from content-drafts.md
**Location**: `/home/rpiplewar/fast_dot_ai/poasting/content-drafts.md`
**Identify**:
- All content variations awaiting scoring
- Look for `[To be filled by Scorer agent]` placeholders
- Extract content text and bias targeting info
### Step 2: Score Each Variation
**For each content piece, calculate**:
#### Framework 1: Gap Selling (0-10 points)
- **Problem Clarity** (0-3): Is problem explicit and relatable?
- **Emotional Impact** (0-3): Is pain point vivid and resonant?
- **Solution Value** (0-4): Is future state compelling and actionable?
#### Framework 2: Cognitive Biases (0-10+ points)
- **Count activated biases** from Munger's 25
- **Lollapalooza bonus**: +2 if 5+ biases converge
- **List specific biases** detected
#### Framework 3: Decision Framework (0-10 points)
- **Hook Strength** (0-3): Does first line grab attention?
- **Content Value** (0-4): Are insights actionable and transferable?
- **CTA Clarity** (0-3): Is next step crystal clear?
**Total Score = Gap (0-10) + Biases (0-10+) + Decision (0-10)**
### Step 3: Assign Pass/Fail Verdict
**Quality Thresholds**:
- **< 20**: ❌ FAIL (filter out)
- **20-24**: ✅ PASS (needs improvement)
- **25-27**: ✅ PASS (GOOD)
- **28-30**: ✅ PASS (EXCELLENT)
### Step 4: Update content-drafts.md
**Replace** `[To be filled by Scorer agent]` with:
```markdown
**Scores:**
- Gap Selling: X/10 (Problem: X/3, Impact: X/3, Solution: X/4)
- Biases Activated: Y (List: Bias1, Bias2, Bias3...)
- Decision Framework: Z/10 (Hook: X/3, Value: X/4, CTA: X/3)
- **TOTAL: XX/30** {✅ PASS or ❌ FAIL}
```
## Validation Checklist
Before marking scoring complete:
- [ ] All variations scored
- [ ] All subscores documented with reasoning
- [ ] Bias lists include specific bias names (not just count)
- [ ] Lollapalooza bonus applied where applicable (5+ biases)
- [ ] Pass/Fail verdicts assigned (< 20 = FAIL, ≥ 20 = PASS)
- [ ] content-drafts.md updated with complete scores
- [ ] Scoring formulas followed exactly per scorer.md
## Example Output
```
✅ Scoring Complete
Variations Scored: 25 (5 themes × 5 variations)
Score Distribution:
- EXCELLENT (28-30): 3 pieces
- GOOD (25-27): 8 pieces
- PASS (20-24): 10 pieces
- FAIL (< 20): 4 pieces
Pass Rate: 84% (21/25)
Highest Scoring:
1. Theme: First Money From Code, Variation 1 (Bold Statement) - 28/30
2. Theme: The Quit Day, Variation 5 (Lollapalooza) - 27/30
3. Theme: Personal Pain → Product, Variation 2 (Story Hook) - 26/30
Output File: content-drafts.md (updated with all scores)
Next Step: Run /content-critic-review for quality feedback
```
## Error Handling
**If scoring logic unclear**:
- Refer to detailed rubrics in `agents/scorer.md`
- Use examples as reference
- Document edge cases for future refinement
**If scores seem inaccurate**:
- Cross-check against manual evaluation
- Verify detection patterns
- Adjust formulas if systematic drift detected
## Accuracy Targets
**Goal**: Within ±2 points (10% margin) of manual expert evaluation
**If accuracy drifts**:
- Review scoring logic against actual performance
- Adjust detection patterns
- Document refinements in scorer.md
## Next Steps
After successful scoring:
1. Review score distribution in content-drafts.md
2. Run `/content-critic-review` to get improvement suggestions
3. Or continue with full pipeline if running `/content-full-pipeline`