This is a production-ready Claude Project for measuring positioning clarity across company materials using cognitive science principles and advanced system prompt engineering.
Quantify positioning drift before it damages brand coherence and market understanding. Companies invest millions in positioning strategy, then watch it silently fragment as different teams create content over time. This system makes that drift measurable and fixable.
Input: Upload 2+ company documents (pitch deck, website copy, sales materials)
Analysis: Multi-dimensional assessment across three core dimensions:
- Consistency (0-33 pts) — Do materials emphasize the same core concepts?
- Focus (0-33 pts) — Is messaging concentrated or fragmented?
- Alignment (0-34 pts) — Do materials support the same strategic positioning?
Output:
- Concept Clarity Score (0-100)
- Top 3-5 divergence points with specific textual evidence
- Actionable recommendations prioritized by business impact
- Strategic implications connecting clarity issues to business outcomes
This system follows KnowledgeForge 4.0 methodology with behavior-focused agents and complete upfront specifications:
00_Project_Instructions.md — Primary system prompt
- Agent modes (Navigator, Assessment, Scoring, Recommendation)
- Response patterns and scoring methodology
- Quality standards and constraints
- Session state management
01_Navigator_Agent.md — Intent interpretation and routing
- Document type recognition
- Analysis depth determination
- Handoff protocol to assessment engine
- Context preservation patterns
02_Clarity_Assessment_Engine.md — Multi-dimensional analysis
- Concept extraction protocol
- Divergence detection (5 types)
- Dimension scoring (consistency, focus, alignment)
- Evidence standards and quality controls
03_Scoring_Coordinator.md — Score synthesis and reporting
- Dimension aggregation and normalization
- Divergence prioritization by business impact
- Report generation with strategic implications
- Recommendation frameworks
04_Knowledge_Base.md — Cognitive science foundation
- 79KB of communication clarity research
- Working memory constraints and attention patterns
- Language optimization techniques
- 100+ psychology studies informing the framework
05_Quick_Reference.md — Patterns and checklists
- Core workflows and decision trees
- Scoring quick reference
- Evidence standards
- Fix patterns and quality checklists
Project Name: Concept Clarity Measurement System
Project Description:
Quantifies positioning clarity across company materials using cognitive science.
Analyzes website, pitch deck, and sales materials to measure:
• Consistency - Same core concepts emphasized?
• Focus - Messaging concentrated or fragmented?
• Alignment - Materials support same strategy?
Outputs: Concept Clarity Score (0-100) + specific divergence examples with
recommendations.
Built on 100+ psychology studies. Used with actual consulting clients.
Add these files to Project Knowledge:
00_Project_Instructions.md(required - core behavior)04_Knowledge_Base.md(required - research foundation)01_Navigator_Agent.md(optional - reference for routing)02_Clarity_Assessment_Engine.md(optional - reference for analysis)03_Scoring_Coordinator.md(optional - reference for scoring)05_Quick_Reference.md(optional - reference for patterns)
Minimum viable: Just 00_Project_Instructions.md + 04_Knowledge_Base.md
Recommended: All six files for complete methodology reference
Use this as your Project Instructions:
You are a Strategic Positioning Clarity Analyst operating within the Concept Clarity Measurement System.
Follow the complete methodology in 00_Project_Instructions.md:
UNDERSTAND → ANALYZE → SCORE → SPECIFY → RECOMMEND
When users upload documents:
1. Identify document types and analysis depth (Navigator mode)
2. Extract positioning concepts and detect divergences (Assessment mode)
3. Calculate multi-dimensional scores (Scoring mode)
4. Generate actionable recommendations (Recommendation mode)
Always provide:
- Concept Clarity Score (0-100) with dimension breakdown
- Top 3-5 divergences with specific quotes as evidence
- Business impact analysis
- Prioritized recommendations
Reference 04_Knowledge_Base.md for cognitive science principles.
Reference agent specifications (01-03) for detailed methodology.
Reference 05_Quick_Reference.md for patterns and standards.
Measure consistency. Quantify clarity. Enable improvement.-
Upload documents (2-3 recommended minimum)
- Pitch deck
- Website homepage copy
- Sales one-pager or materials
-
Receive analysis
- Concept Clarity Score
- Dimension scores (consistency, focus, alignment)
- Top divergences with specific evidence
- Strategic implications
-
Implement fixes
- Prioritize by impact
- Address high-impact divergences first
- Update materials systematically
-
Re-assess quarterly
- Track improvement over time
- Catch new drift early
- Maintain clarity as you scale
User: uploads pitch_deck.pdf, website_homepage.docx, sales_onepager.pdf
System Response:
Analyzing 3 documents for positioning clarity...
**Documents Received:**
- pitch_deck.pdf — Investor presentation
- website_homepage.docx — Customer-facing copy
- sales_onepager.pdf — Sales enablement
## Concept Clarity Score: 62/100
### Dimension Breakdown:
- **Consistency**: 18/33 — Core concepts present but emphasis varies significantly
- **Focus**: 23/33 — Materials cover 5-6 themes with moderate dilution
- **Alignment**: 21/34 — Strategic narratives overlap but diverge on key points
### Top Divergence Points:
**1. Primary Value Proposition Conflict** (Impact: High)
- **Issue**: Three different value propositions presented as primary
- **Evidence**:
- Pitch Deck: "Reduce operational costs by 40% with AI automation"
- Website: "Transform customer experience with intelligent workflows"
- Sales One-Pager: "Enterprise-grade security meets seamless integration"
- **Recommendation**: Select one primary value prop (e.g., cost reduction), position others as secondary benefits
[...continues with remaining divergences, strategic implications, and next steps]This system demonstrates core KnowledgeForge principles:
1. Behavior Over Personality
- Agents define what they DO, not what they ARE
- "Extract concepts and detect divergences" not "I'm a helpful analyst"
2. Complete Upfront Specifications
- 10,000+ lines of methodology before first run
- Every agent has purpose, capabilities, constraints, integration points
3. Multi-Agent Coordination
- Hierarchical pattern: Navigator → Assessment → Scoring → Output
- Clear handoffs with context preservation
- Sequential execution with explicit boundaries
4. Pattern Synthesis
- Cognitive science + measurement theory + practical consulting experience
- 100+ psychology studies inform analysis methodology
- Real-world testing across actual client engagements
5. Quantitative Measurement
- Transforms qualitative assessment into quantified scores
- Reproducible methodology produces consistent results
- Evidence-based divergence detection prevents subjective bias
Navigator Agent (Routing & Intent)
↓
Clarity Assessment Engine (Analysis & Extraction)
↓
Scoring Coordinator (Synthesis & Reporting)
↓
User Output (Markdown Report)
Sequential with state preservation:
- Navigator completes → passes context to Assessment
- Assessment completes → passes analysis to Coordinator
- Coordinator completes → generates final report
Cognitive Science Foundation (04_Knowledge_Base.md):
- Working memory constraints (Miller's 7±2)
- Cognitive load optimization (Sweller, Cowan)
- Comprehension science principles
- Language clarity research
Applied to business context:
- Positioning consistency measurement
- Message fragmentation detection
- Strategic alignment verification
This system is actively deployed for:
✅ Consulting Engagements — Analyzing client positioning clarity ✅ Strategic Planning — Pre-fundraise messaging audits ✅ Content Governance — Quarterly clarity tracking ✅ Team Alignment — Resolving cross-functional messaging conflicts
Typical Results:
- Clarity scores improve 15-25 points within one quarter
- Sales cycle length decreases as messaging confusion reduces
- Conversion rates improve as positioning becomes clearer
- Team velocity increases with shared positioning guidelines
Research Foundation:
- 100+ peer-reviewed psychology studies
- Cognitive load theory (Sweller, Paas)
- Working memory research (Cowan, Baddeley)
- Comprehension science (Kintsch, van Dijk)
Real-World Testing:
- Used with 10+ consulting clients
- Tested across industries (SaaS, fintech, healthcare tech)
- Validated with companies from seed to Series C
- Refined through 50+ analysis iterations
Measurement Reliability:
- Consistent scores on repeat analysis (±3 points)
- Inter-rater reliability when multiple analysts review
- Divergences align with real confusion in sales conversations
- Score improvements correlate with business metric improvements
What this system measures:
- ✅ Positioning consistency across materials
- ✅ Message focus vs. fragmentation
- ✅ Strategic narrative alignment
What this system does NOT measure:
- ❌ Quality of ideas or strategy
- ❌ Competitive positioning strength
- ❌ Market opportunity size
- ❌ Messaging effectiveness in isolation
Best used for:
- Companies with 2+ years of content creation
- Organizations with multiple content creators
- Teams experiencing sales friction due to messaging confusion
- Companies preparing for fundraising or major launches
Less useful for:
- Very early-stage companies (< 1 year, minimal content)
- Companies with single content creator (consistency easier)
- Completely new positioning (nothing to measure consistency against)
Adjust in 02_Clarity_Assessment_Engine.md:
- Concept categories (add industry-specific positioning elements)
- Evidence weighting (emphasize different proof points)
- Divergence types (add industry-specific inconsistency patterns)
Adjust in 01_Navigator_Agent.md:
- Analysis mode triggers (quick_scan vs standard vs deep_dive)
- Document requirements (minimum viable set)
- Follow-up suggestions (complementary materials)
Adjust in 03_Scoring_Coordinator.md:
- Dimension weights (if consistency more important than focus)
- Score interpretation bands (stricter or looser thresholds)
- Divergence prioritization (different impact factors)
This methodology is actively refined through production use. Improvements welcome:
- Issue: Describe the use case or limitation
- Discussion: Explain the proposed enhancement
- Specification: Follow KnowledgeForge templates
- Validation: Include test scenarios
Areas particularly valuable:
- Additional divergence types and detection patterns
- Industry-specific customizations
- Score calibration refinements
- Integration with content management systems
MIT License - See LICENSE file
This framework is freely available for:
- Personal use
- Commercial consulting work
- Building derivative tools
- Academic research
Attribution appreciated but not required.
Token Usage:
- Average analysis: ~5,000 tokens (input) + ~2,500 tokens (output)
- Deep dive analysis: ~8,000 tokens (input) + ~4,000 tokens (output)
- Total system specification: ~35,000 tokens across all files
Performance:
- Analysis time: 30-90 seconds for 2-3 documents
- Consistency: ±3 points on repeat analysis
- Throughput: ~20 analyses per hour (Claude Sonnet)
Requirements:
- Claude Projects (Anthropic) - Pro or Team tier
- 2+ documents minimum for meaningful measurement
- Documents should be recent (within 6 months ideally)
- GitHub Issues: Technical questions and bug reports
- Consulting: Professional positioning clarity services
- Methodology: Questions about KnowledgeForge or this implementation
Built for the AI Tinkerers community 🎄
Demonstrated at AI Tinkerers Holiday Science Fair, December 2024
5-Minute Setup:
- Create Claude Project
- Upload
00_Project_Instructions.md+04_Knowledge_Base.md - Set custom instructions (template above)
- Upload your first set of documents
- Receive Concept Clarity Score + divergence analysis
First Analysis:
- Upload pitch deck + website copy + sales materials
- System automatically routes to standard analysis
- Receive score, divergences, and recommendations
- Implement high-impact fixes first
Ongoing Use:
- Re-assess quarterly after content updates
- Track score improvements over time
- Catch positioning drift before it damages brand
- Maintain clarity as your company scales
Keep your positioning as clear on Day 365 as it was on Day 1.
Built with KnowledgeForge 4.0 | Cognitive Science + AI + Real Business Problems
This tool is part of the SEMalytics research portfolio—applying cognitive science to make communications land.
The problem: You know what you mean. Your audience doesn't always get it. This system quantifies the gap and shows you exactly where clarity breaks down.
Related Work:
- Communications Optimization System (COS) — Personality-aware content analysis for B2B sales and marketing
- KnowledgeForge — The agent orchestration methodology powering this system
Built by SEMalytics · Making messages land.