Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Synthesize competing positions through structured thesis-antithesis-synthesis process. Use when stakeholders disagree, trade-offs exist, or multiple valid perspectives need integration. Produces integrated positions with acknowledged trade-offs.
.claude/skills/aiskillstore-reasoning-dialectical/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 25% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 42% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 117% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 191% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 94% | 0% |
Synthesize opposing views into higher-order resolution. The logic of productive disagreement.
Dialectical : Thesis → Antithesis → Synthesis
Where:
Thesis : Position × Evidence × Stakeholder → ArgumentA
Antithesis : ArgumentA → CounterPosition × Evidence × Stakeholder → ArgumentB
Synthesis : (ArgumentA, ArgumentB) → IntegratedPosition × TradeoffsUse dialectical when:
Don't use when:
Each position must be represented at its strongest:
Synthesis is NOT:
Synthesis IS:
Purpose: Articulate first position at maximum strength.
Components:
yamlthesis: position: statement: "Core claim being made" underlying_concern: "What this position is really about" stakeholder: who: "Person/team holding this view" role: "Their organizational function" incentives: "What they optimize for" evidence: supporting: - claim: "Evidence point" source: "Where this comes from" strength: 0.0-1.0 empirical: [DataPoint] logical: [Argument] implications: if_adopted: "What happens if we go this way" risks: [Risk] benefits: [Benefit]
Example:
yamlthesis: position: statement: "We should prioritize enterprise features over SMB growth" underlying_concern: "Revenue concentration and deal size efficiency" stakeholder: who: "Sales leadership" role: "Revenue generation" incentives: "ARR, deal size, quota attainment" evidence: supporting: - claim: "Enterprise deals average $400K vs SMB $5K" source: "Q3 sales data" strength: 0.95 - claim: "Sales cost per $ revenue 5x lower for enterprise" source: "CAC analysis" strength: 0.85 empirical: - "3 enterprise deals = entire SMB revenue" - "Enterprise churn 3% vs SMB 8%" implications: if_adopted: "Focus engineering on enterprise features, reduce SMB investment" risks: - "Lose SMB market to competitors" - "Revenue concentration risk" benefits: - "Higher margins" - "Larger average deal"
Purpose: Articulate counter-position at maximum strength.
Process:
Components:
yamlantithesis: position: statement: "Counter claim" underlying_concern: "What this position is really about" stakeholder: who: "Person/team holding this view" role: "Their organizational function" incentives: "What they optimize for" critique_of_thesis: - assumption_challenged: "Thesis assumes X" counter_evidence: "But actually Y" - risk_identified: "Thesis ignores Z" evidence: supporting: [EvidencePoint] empirical: [DataPoint] logical: [Argument] implications: if_adopted: "What happens if we go this way" risks: [Risk] benefits: [Benefit]
Example:
yamlantithesis: position: statement: "SMB volume creates the foundation for sustainable growth" underlying_concern: "Market presence, product iteration, and risk distribution" stakeholder: who: "Product leadership" role: "Product-market fit and growth" incentives: "Usage, retention, feature validation" critique_of_thesis: - assumption_challenged: "Enterprise features drive growth" counter_evidence: "SMB usage generates product insights 10x faster" - assumption_challenged: "Revenue concentration is acceptable" counter_evidence: "Losing 1 enterprise deal = losing 80 SMB accounts" - risk_identified: "Enterprise sales cycle is 9 months" evidence: supporting: - claim: "SMB accounts generate 80% of feature requests" source: "Product feedback analysis" strength: 0.90 - claim: "SMB provides faster iteration cycles" source: "Release metrics" strength: 0.85 empirical: - "SMB churn prediction accuracy 95% vs enterprise 60%" - "Product improvements from SMB feedback shipped in 2 weeks" implications: if_adopted: "Maintain SMB investment, use as product lab" risks: - "Slower revenue growth short-term" - "Lower margin overall" benefits: - "Diversified revenue base" - "Faster product iteration" - "Lower concentration risk"
Purpose: Integrate positions at higher level, resolving underlying tensions.
Synthesis Approaches:
| Approach | When to Use | Example | |----------|-------------|---------| | Integration | Both positions address valid concerns | "Enterprise revenue + SMB as product lab" | | Sequencing | Temporal resolution possible | "SMB first for PMF, then enterprise scale" | | Segmentation | Different contexts warrant different approaches | "SMB for product X, Enterprise for product Y" | | Reframing | Original dichotomy was false | "The real question isn't SMB vs Enterprise, it's time-to-value" | | Transcendence | Higher goal subsumes both | "Optimize for sustainable unit economics regardless of segment" |
Synthesis Components:
yamlsynthesis: integrated_position: statement: "What we will actually do" framing: "How this resolves the tension" how_thesis_is_addressed: concern_validated: "What's true about thesis" how_incorporated: "How we address that concern" how_antithesis_is_addressed: concern_validated: "What's true about antithesis" how_incorporated: "How we address that concern" trade_offs_acknowledged: - trade_off: "What we're giving up" mitigation: "How we reduce impact" accepted_by: "Stakeholder who accepts this" resolution_type: integration | sequencing | segmentation | reframing | transcendence implementation: actions: [Action] metrics: [Metric] # How we know it's working review_date: date # When we reassess
Example:
yamlsynthesis: integrated_position: statement: "SMB as rapid learning engine, enterprise as revenue engine, with explicit feature graduation path" framing: "Not SMB vs Enterprise, but learning velocity vs revenue efficiency with a bridge between them" how_thesis_is_addressed: concern_validated: "Enterprise deals are more efficient per dollar" how_incorporated: "Maintain enterprise sales motion, prioritize enterprise features that have been validated through SMB" how_antithesis_is_addressed: concern_validated: "SMB generates faster product learning" how_incorporated: "Protect SMB investment as product lab, use SMB metrics to prioritize enterprise features" trade_offs_acknowledged: - trade_off: "Some enterprise-only features will ship slower" mitigation: "Identify 'must have' enterprise features, fast-track those" accepted_by: "Sales leadership (with fast-track list)" - trade_off: "Some SMB features won't graduate to enterprise" mitigation: "Clear graduation criteria defined upfront" accepted_by: "Product leadership (with criteria agreement)" resolution_type: integration implementation: actions: - "Define feature graduation criteria (Product + Sales)" - "Create SMB → Enterprise feature pipeline" - "Allocate 60% engineering to graduated features, 40% to SMB lab" metrics: - "SMB feature graduation rate (target: 3/month)" - "Enterprise close rate on graduated features (target: +20%)" - "Combined revenue growth (target: 30% QoQ)" review_date: "End of Q2"
| Gate | Requirement | Failure Action | |------|-------------|----------------| | Thesis strength | Steel-manned, evidence-backed | Strengthen before proceeding | | Antithesis genuine | Not straw-man, different stakeholder | Find genuine opposition | | Synthesis integrative | Not compromise or victory | Reframe until true synthesis | | Trade-offs explicit | All parties acknowledge costs | Surface hidden disagreements | | Actionable | Concrete next steps | Add implementation detail |
Synthesis isn't complete until affected stakeholders acknowledge:
yamlstakeholder_acknowledgment: thesis_stakeholder: name: "Sales leadership" concern_understood: true synthesis_addresses_concern: true accepts_trade_offs: true conditions: "Fast-track list for critical enterprise features" antithesis_stakeholder: name: "Product leadership" concern_understood: true synthesis_addresses_concern: true accepts_trade_offs: true conditions: "Clear graduation criteria before implementation"
| Failure | Symptom | Fix | |---------|---------|-----| | False dichotomy | Positions aren't truly opposed | Reframe the actual tension | | Straw-man | Weak representation of one side | Involve actual stakeholder | | Mushy middle | Synthesis is just "do both" | Force resource allocation | | Unacknowledged loss | Trade-offs hidden | Surface what's being given up | | No implementation | Synthesis is abstract | Add concrete actions |
yamldialectical_output: thesis: position: string stakeholder: string evidence: [EvidencePoint] strength: float # 0.0-1.0 antithesis: position: string stakeholder: string evidence: [EvidencePoint] strength: float synthesis: position: string resolution_type: string confidence: float integration: thesis_addressed: string antithesis_addressed: string trade_offs: - trade_off: string mitigation: string accepted_by: string stakeholder_agreement: - stakeholder: string agrees: bool conditions: optional<string> implementation: actions: [string] metrics: [string] review_date: date next: suggested_mode: ReasoningMode # Usually causal canvas_updates: [string] trace: duration_ms: int rounds_of_refinement: int
Context: "Engineering wants to rebuild core platform (6 months). Sales wants new features for Q2 deals."
Stage 1 - Thesis (Engineering):
Position: "Technical debt is blocking velocity. Rebuild now or pay 10x later."
Evidence:
- Deploy time increased 300% YoY
- 40% of sprint spent on workarounds
- 3 critical bugs from architecture issues
Underlying concern: Sustainable development velocityStage 2 - Antithesis (Sales):
Position: "We have $2M in pipeline dependent on Q2 features. Delay = lose deals."
Evidence:
- 5 enterprise deals waiting on specific features
- Competitor launching similar features in March
- Q2 quota at risk without new capabilities
Underlying concern: Revenue target attainmentStage 3 - Synthesis:
Integrated position: "Strangler fig pattern - rebuild incrementally while
delivering high-priority features"
How thesis addressed: Platform rebuild happens, but in modules alongside features
How antithesis addressed: Q2 features delivered, no delay
Trade-offs:
- Rebuild takes 9 months instead of 6 (Engineering accepts)
- Only top 3 features in Q2, not all 5 (Sales accepts with prioritization input)
Resolution type: Integration via sequencing
Implementation:
- Week 1: Joint prioritization session (top 3 features + first rebuild module)
- Q2: Deliver features on new modules where possible
- Q3-Q4: Complete rebuild with feature delivery continuing| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 46,047 | 35,866 | -22% | 1 | 1 | 0% | 7,119 | 8,883 | +25% | 0 | 0 | — |
case-02 | pass→pass | 38,301 | 29,306 | -23% | 1 | 1 | 0% | 6,015 | 8,773 | +46% | 0 | 0 | — |
case-03 | fail→fail | 19,863 | 33,703 | +70% | 1 | 1 | 0% | 2,135 | 6,477 | +203% | 0 | 0 | — |
case-04 | fail→pass | 33,698 | 22,190 | -34% | 1 | 1 | 0% | 4,297 | 6,121 | +42% | 0 | 0 | — |
case-05 | fail→fail | 17,840 | 25,324 | +42% | 1 | 1 | 0% | 1,990 | 6,135 | +208% | 0 | 0 | — |
case-06 | fail→fail | 21,556 | 36,814 | +71% | 1 | 1 | 0% | 1,986 | 6,605 | +233% | 0 | 0 | — |
case-07 | fail→fail | 29,316 | 46,966 | +60% | 1 | 1 | 0% | 2,130 | 7,096 | +233% | 0 | 0 | — |
case-08 | fail→fail | 29,164 | 25,077 | -14% | 1 | 1 | 0% | 2,264 | 6,167 | +172% | 0 | 0 | — |
case-09 | fail→pass | 27,970 | 32,087 | +15% | 1 | 1 | 0% | 3,120 | 6,766 | +117% | 0 | 0 | — |
case-10 | fail→pass | 24,610 | 29,840 | +21% | 1 | 1 | 0% | 2,523 | 7,352 | +191% | 0 | 0 | — |
case-11 | fail→pass | 37,977 | 23,487 | -38% | 1 | 1 | 0% | 3,067 | 5,962 | +94% | 0 | 0 | — |
case-12 | pass→pass | 39,200 | 36,336 | -7% | 1 | 1 | 0% | 3,362 | 8,377 | +149% | 0 | 0 | — |
case-13 | fail→pass | 65,878 | 22,984 | -65% | 1 | 1 | 0% | 3,484 | 6,134 | +76% | 0 | 0 | — |
case-14 | fail→pass | 36,384 | 35,465 | -3% | 1 | 1 | 0% | 2,677 | 6,747 | +152% | 0 | 0 | — |
case-15 | fail→pass | 22,570 | 24,260 | +7% | 1 | 1 | 0% | 2,387 | 6,555 | +175% | 0 | 0 | — |
case-16 | fail→fail | 40,703 | 57,193 | +41% | 1 | 1 | 0% | 3,162 | 6,360 | +101% | 0 | 0 | — |
case-17 | fail→pass | 24,060 | 40,290 | +67% | 1 | 1 | 0% | 2,877 | 6,506 | +126% | 0 | 0 | — |
case-18 | fail→fail | 59,851 | 43,637 | -27% | 1 | 1 | 0% | 3,547 | 6,735 | +90% | 0 | 0 | — |
case-19 | pass→pass | 32,553 | 35,317 | +8% | 1 | 1 | 0% | 4,659 | 6,172 | +32% | 0 | 0 | — |
case-20 | pass→fail | 22,092 | 31,216 | +41% | 1 | 1 | 0% | 2,814 | 6,739 | +139% | 0 | 0 | — |
case-21 | pass→fail | 18,017 | 21,315 | +18% | 1 | 1 | 0% | 2,993 | 6,593 | +120% | 0 | 0 | — |
case-22 | pass→fail | 20,975 | 24,857 | +19% | 1 | 1 | 0% | 2,330 | 7,054 | +203% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +27 percentage points is the difference between those two pass rates over the 22 comparable cases. 3 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.