Agent skill

ensemble-content-scorer

Multi-model consensus scoring for content ideas. Scores the same idea with Claude, GPT-4o, Gemini, and Grok in parallel, then aggregates for a balanced verdict. Reduces single-model bias and improves viral predictions.

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npx add-skill https://github.com/drshailesh88/integrated_content_OS/tree/main/skills/cardiology/ensemble-content-scorer

SKILL.md

Ensemble Content Scorer

Wisdom of crowds, but for AI. This skill scores your content ideas using multiple AI models, then aggregates for consensus. More reliable than single-model predictions.

WHAT IT DOES

                Content Idea
                     │
    ┌────────────────┼────────────────┐
    │                │                │
    ▼                ▼                ▼
[Claude]        [GPT-4o]         [Gemini]
  Score            Score            Score
    │                │                │
    └────────────────┼────────────────┘
                     │
                     ▼
            [Aggregator (Claude)]
                     │
                     ▼
         Consensus Score + Verdict

WHY MULTI-MODEL?

Single Model Ensemble
May have biases Biases cancel out
One perspective Multiple perspectives
Black box score Transparent reasoning
May miss nuances Catches different angles

TRIGGERS

Use this skill when you say:

  • "Score this content idea"
  • "Is this topic worth pursuing?"
  • "Rate my video concept"
  • "Predict if this will go viral"
  • "Ensemble score: [topic]"

USAGE

In Claude Code (Recommended)

"Ensemble score: Statins myth-busting for Indian audience"

"Score this video idea: Why your LDL target depends on your risk"

"Rate these ideas and rank them:
1. GLP-1 agonists explained
2. Heart attack warning signs
3. Is coconut oil heart-healthy?"

CLI Mode

bash
# Score single idea
python scripts/score_content.py --idea "Statins myth-busting for Indian audience"

# Score multiple ideas
python scripts/score_content.py --ideas "GLP-1 explained" "Statin myths" "CAC scoring"

# Use specific models
python scripts/score_content.py --idea "Topic" --models claude,gpt4o,gemini

SCORING DIMENSIONS

Each model scores on these dimensions (1-10):

Dimension What It Measures
Relevance How relevant to target audience (Indian patients/doctors)
Novelty How fresh is the angle? Been covered before?
Expertise Match Does it match your expertise as interventional cardiologist?
Engagement Potential Will it capture and hold attention?
Share-ability Will people share this? Controversy potential?
Evergreen Factor Will this be relevant in 6 months?

Total Score: 0-60

OUTPUT FORMAT

markdown
# ENSEMBLE CONTENT SCORE

**Idea:** Statins myth-busting for Indian audience - why most "side effects" aren't real

**Date:** 2025-01-01

---

## INDIVIDUAL MODEL SCORES

### Claude (Anthropic)
| Dimension | Score | Reasoning |
|-----------|-------|-----------|
| Relevance | 9/10 | High - statins widely prescribed in India, misinformation common |
| Novelty | 7/10 | Topic covered before, but Indian-specific angle is fresher |
| Expertise | 9/10 | Perfect for interventional cardiologist |
| Engagement | 8/10 | Controversial enough to spark discussion |
| Shareability | 8/10 | Will trigger debates |
| Evergreen | 9/10 | Statin myths persist |
| **Total** | **50/60** | |

### GPT-4o (OpenAI)
| Dimension | Score | Reasoning |
|-----------|-------|-----------|
| Relevance | 9/10 | Very relevant for Indian audience |
| Novelty | 6/10 | Many statin videos exist |
| Expertise | 10/10 | Perfect fit |
| Engagement | 9/10 | Myth-busting format works |
| Shareability | 8/10 | Good controversy factor |
| Evergreen | 8/10 | Will stay relevant |
| **Total** | **50/60** | |

### Gemini (Google)
| Dimension | Score | Reasoning |
|-----------|-------|-----------|
| Relevance | 8/10 | Good for health-conscious Indians |
| Novelty | 7/10 | Indian angle adds freshness |
| Expertise | 9/10 | Great fit |
| Engagement | 7/10 | Educational more than viral |
| Shareability | 7/10 | Moderate share potential |
| Evergreen | 9/10 | Long-lasting relevance |
| **Total** | **47/60** | |

---

## CONSENSUS SCORE

| Model | Total Score |
|-------|-------------|
| Claude | 50/60 |
| GPT-4o | 50/60 |
| Gemini | 47/60 |
| **Average** | **49/60 (81.7%)** |
| **Std Dev** | 1.7 (High Consensus) |

---

## VERDICT

🟢 **STRONG PURSUE** (Score: 49/60, Consensus: High)

All models agree this is a strong content idea. The combination of:
- High relevance to your audience
- Perfect expertise match
- Good controversy factor
- Evergreen potential

Makes this a priority topic for your content calendar.

---

## RECOMMENDATIONS

1. **Angle Enhancement**: Focus on the "nocebo effect" - most statin "side effects" are psychosomatic
2. **Hook Suggestion**: "90% of statin side effects aren't real - here's the data"
3. **Format**: 12-15 minute deep dive with studies
4. **Hinglish Tip**: Use "side effect ka drama" for relatability

---

## DISSENT ANALYSIS

- **Gemini** scored lower on engagement (7 vs 8-9)
- Suggests: May need stronger hook to maximize viral potential
- Consider: Adding patient testimonial or counter-narrative

SCORING TIERS

Score Range Verdict Action
50-60 🟢 STRONG PURSUE High priority, create immediately
40-49 🟡 WORTH PURSUING Good idea, add to calendar
30-39 🟠 NEEDS REFINEMENT Has potential, needs angle work
20-29 🔴 RECONSIDER Weak idea, low priority
0-19 ⛔ SKIP Not worth the effort

CONSENSUS INTERPRETATION

Std Deviation Interpretation
< 3 High consensus - models agree
3-5 Moderate consensus - some disagreement
> 5 Low consensus - divisive idea (may be worth exploring!)

INTEGRATION

Enhances:

  • viral-content-predictor - More reliable predictions
  • youtube-script-master - Validate topics before scripting
  • content-repurposer - Know which content to repurpose

Workflow:

Idea Generation → Ensemble Score → [High Score?] → Create Content
                         ↓
                   [Low Score?] → Refine or Skip

MODELS USED

Model Provider Cost Notes
Claude Sonnet Anthropic Subscription Your primary
GPT-4o OpenAI API Strong analysis
Gemini Pro Google FREE Good for fact-checking
Grok xAI API Twitter trend awareness

Minimum required: 2 models (Claude + one other) Recommended: 3+ models for robust consensus

DEPENDENCIES

python
anthropic>=0.18.0
openai>=1.0.0           # For GPT-4o
google-generativeai>=0.3.0  # For Gemini
python-dotenv>=1.0.0
rich>=13.0.0

API KEYS NEEDED

Key Purpose Status
ANTHROPIC_API_KEY Claude Already have
OPENAI_API_KEY GPT-4o Already have
GOOGLE_API_KEY Gemini Already have
XAI_API_KEY Grok (optional) Already have

BATCH SCORING

For scoring multiple ideas at once:

bash
python scripts/score_content.py --batch \
    --ideas "GLP-1 for heart failure" \
            "Statin myth-busting" \
            "CAC scoring guide" \
            "Why LDL matters" \
            "Exercise for heart health"

Output:

| Rank | Idea | Score | Verdict |
|------|------|-------|---------|
| 1 | Statin myth-busting | 49/60 | 🟢 STRONG PURSUE |
| 2 | GLP-1 for heart failure | 45/60 | 🟡 WORTH PURSUING |
| 3 | CAC scoring guide | 42/60 | 🟡 WORTH PURSUING |
| 4 | Why LDL matters | 38/60 | 🟠 NEEDS REFINEMENT |
| 5 | Exercise for heart health | 35/60 | 🟠 NEEDS REFINEMENT |

NOTES

  • Speed: ~30 seconds for single idea (parallel API calls)
  • Cost: Minimal - short prompts to each model
  • Reliability: Consensus typically more accurate than single model
  • When to ignore: If YOU have strong conviction, trust your expertise

This skill helps you invest your time in content that's more likely to succeed.

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