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Get Started Free →Build, evaluate, and stress-test a Business Model Canvas (Osterwalder) across all 9 blocks. Use when designing or refreshing a business model, auditing a canvas for gaps, exploring monetization, or aligning on the model's assumptions.
.claude/skills/borghei-business-model-canvas/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 105% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 33% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 60% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 6% | 0% |
| case-05 | ✓→✓ | = Same ✓ | 63% | 0% |
A working Business Model Canvas (BMC) — Alexander Osterwalder's 9-block strategic management template that captures how an organization creates, delivers, and captures value.
Before building the canvas, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
Start with Customer Segments and Value Propositions (these drive everything else). Then fill: Channels, Customer Relationships, Revenue Streams. Then: Key Resources, Activities, Partnerships. Finish with Cost Structure.
For each Customer Segment, trace: Segment → Value Prop → Channel → Relationship → Revenue. If you can't connect these, the model has a gap.
For each block, list the top 2-3 assumptions and rate (high / medium / low) on:
canvas_validator.pyAudit the canvas for: empty blocks, ungrounded value-prop / segment matches, revenue / cost imbalance, segment-channel-relationship coherence.
bashpython3 project-management/strategy-frameworks/business-model-canvas/scripts/canvas_validator.py \ --input canvas.json --format markdown
Most first drafts are wrong in interesting ways. Plan to revise 3-5 times.
| Pattern | Examples | Characteristics | |---------|----------|-----------------| | Unbundled | Investment banking (advisor + product) | Different segments; different value props | | Long Tail | Netflix, Amazon | Niche x volume | | Multi-sided platform | Visa, Airbnb | Connects 2+ segments; network effects | | Free / Freemium | Spotify, LinkedIn | One segment pays for another's free use | | Open | Open-source + services | Free product, paid expertise/services |
Most modern SaaS = multi-sided OR freemium variant.
| Cost-driven | Value-driven | |-------------|--------------| | Lean cost structure | Focus on premium value | | Low-price value prop | High-value, often high-price | | Maximum automation | High-touch service | | Extensive outsourcing | In-house excellence |
Most companies need to pick ONE — trying both produces mediocre everything.
After using this skill, you should have:
references/canvas-framework.md — the 9 blocks deep, patterns, examplesreferences/examples-anti-patterns.md — worked examples + common failuresproject-management/strategy-frameworks/lean-canvas — startup-stage variantproject-management/strategy-frameworks/swot-analysis — internal/external strengths-weaknessesproject-management/strategy-frameworks/porters-five-forces — competitive dynamicsproject-management/discovery/value-proposition-canvas — deeper on the value-prop blockproject-management/execution/north-star-metric — what to measure once model is setbusiness-growth/pricing-strategy — pricing depth for the revenue blockc-level-advisor/ceo-advisor — strategic context for the model| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-05 | pass→pass | 18,571 | 21,411 | +15% | 1 | 1 | 0% | 2,824 | 4,612 | +63% | 0 | 0 | — |
case-06 | pass→pass | 26,983 | 30,778 | +14% | 1 | 1 | 0% | 5,558 | 7,639 | +37% | 0 | 0 | — |
case-01 | fail→fail | 37,999 | 38,907 | +2% | 1 | 1 | 0% | 5,905 | 7,598 | +29% | 0 | 0 | — |
case-02 | fail→fail | 40,395 | 38,785 | -4% | 1 | 1 | 0% | 6,014 | 7,131 | +19% | 0 | 0 | — |
case-03 | fail→fail | 31,849 | 34,072 | +7% | 1 | 1 | 0% | 4,626 | 6,510 | +41% | 0 | 0 | — |
case-04 | pass→pass | 21,577 | 25,438 | +18% | 1 | 1 | 0% | 3,173 | 5,196 | +64% | 0 | 0 | — |
case-07 | fail→pass | 15,982 | 23,322 | +46% | 1 | 1 | 0% | 2,468 | 5,067 | +105% | 0 | 0 | — |
case-08 | fail→pass | 24,991 | 22,993 | -8% | 1 | 1 | 0% | 3,807 | 5,068 | +33% | 0 | 0 | — |
case-09 | fail→pass | 15,754 | 14,607 | -7% | 1 | 1 | 0% | 2,231 | 3,576 | +60% | 0 | 0 | — |
case-10 | pass→pass | 18,592 | 18,658 | +0% | 1 | 1 | 0% | 2,566 | 4,016 | +57% | 0 | 0 | — |
case-11 | fail→pass | 10,955 | 2,751 | -75% | 1 | 1 | 0% | 1,782 | 1,892 | +6% | 0 | 0 | — |
case-12 | pass→pass | 11,249 | 12,433 | +11% | 1 | 1 | 0% | 1,612 | 3,132 | +94% | 0 | 0 | — |
case-13 | pass→pass | 12,074 | 12,819 | +6% | 1 | 1 | 0% | 1,775 | 3,394 | +91% | 0 | 0 | — |
case-14 | pass→pass | 9,948 | 10,282 | +3% | 1 | 1 | 0% | 1,381 | 2,826 | +105% | 0 | 0 | — |
case-15 | pass→pass | 7,974 | 17,148 | +115% | 1 | 1 | 0% | 1,144 | 3,974 | +247% | 0 | 0 | — |
case-16 | pass→pass | 10,967 | 15,002 | +37% | 1 | 1 | 0% | 1,618 | 3,762 | +133% | 0 | 0 | — |
case-17 | pass→pass | 11,804 | 11,200 | -5% | 1 | 1 | 0% | 1,815 | 3,130 | +72% | 0 | 0 | — |
case-18 | fail→fail | 8,379 | 6,311 | -25% | 1 | 1 | 0% | 1,343 | 2,487 | +85% | 0 | 0 | — |
case-19 | pass→pass | 4,872 | 2,166 | -56% | 1 | 1 | 0% | 811 | 1,816 | +124% | 0 | 0 | — |
case-20 | pass→pass | 6,203 | 6,003 | -3% | 1 | 1 | 0% | 859 | 2,360 | +175% | 0 | 0 | — |
case-21 | pass→pass | 9,922 | 14,129 | +42% | 1 | 1 | 0% | 1,391 | 3,387 | +143% | 0 | 0 | — |
case-22 | pass→pass | 4,981 | 7,387 | +48% | 1 | 1 | 0% | 703 | 2,518 | +258% | 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 +18 percentage points is the difference between those two pass rates over the 22 comparable cases.
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.