biz-validate
Skill1 starsChanged 7 months agoMITView on GitHub
Runs iterative hypothesis validation loop. Triggers ONLY when: biz-think acid test fails, user explicitly asks to validate a business assumption, or user says to pivot. Do NOT trigger when: discussing business strategy casually or during product development.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- david-vrba/claude-power-skillstheir own version, first seen Jun 27, 2026
Other versions1 project uses a version of this.
Word for word · 0
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Wrote their own version · 1
- david-vrba/claude-power-skills★ 4same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository30 other files it gives its agents.
- claude.mdCLAUDE.md
- biz-thinkSkill
- brand-buildSkill
- community-engageSkill
- content-createSkill
- content-distributeSkill
- copy-craftSkill
- data-decideSkill
- finance-opsSkill
- growth-trackSkill
- infra-opsSkill
- issue-createSkill
- legal-guardSkill
- post-mergeSkill
- pre-codeSkill
- pre-commitSkill
- pre-prSkill
- product-evalSkill
- project-initSkill
- retroSkill
- roadmap-steerSkill
- sales-closeSkill
- search-evalSkill
- self-reviewSkill
- sopSkill
- staging-verifySkill
- support-opsSkill
- test-gateSkill
- ux-auditSkill
- work-breakdownSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 7 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 19
Run this skill when:
- Distinctive: line 107
Always prefer skin-in-the-game data (money, time invested) over opinions (surveys, "I would use this")
- Distinctive: line 109
If an experiment takes more than 1 week, it's too expensive.
- Distinctive: line 110
Search the web for existing data before running your own experiment (someone may have already validated this)
- Very specific: line 132
Kill criteria: if 3+ pivots on the same core idea all fail, kill it entirely.
- Very specific: line 138
After each cycle, update these in auto memory (memory/validation_log.md):
- Distinctive: line 156
No behavioral evidence of willingness to pay after 3 experiment cycles
- Distinctive: line 173
You are almost certainly at Stage 1: Do not skip to Stage 2 thinking.
- Distinctive: line 179
All validated → "Run brand-build, then work-breakdown"
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
biz-validate: Business Hypothesis Validation Loop
A cyclical SOP based on Running Lean (Ash Maurya), Pretotyping (Alberto Savoia), and Hypothesis-Driven Entrepreneurship (HBS). This skill LOOPS — it does not run once and stop.
Framework sources:
- Running Lean 3rd Ed (Ash Maurya) — macro stages: Problem/Solution Fit → Product/Market Fit → Scale
- Pretotyping (Alberto Savoia, Google) — behavioral proof before building
- Reflect-Inquire-Learn (Eisenmann/Ries, HBS) — single experiment cycle
Entry Conditions
Run this skill when:
biz-thinkacid test fails (cannot complete the one-sentence answer)- An assumption in the business model needs validation
- Pivoting after a failed experiment
- User says "validate this" or "test this idea"
The Loop: Reflect → Hypothesize → Experiment → Learn → Update
┌─────────────────────────────────────┐
│ │
▼ │
REFLECT │
What is the riskiest assumption? │
│ │
▼ │
HYPOTHESIZE │
"At least X% of [target] will │
[action] if [condition]" │
│ │
▼ │
EXPERIMENT │
Run the cheapest possible test │
(hours, not weeks) │
│ │
▼ │
LEARN │
Did we hit the threshold? │
│ │
├── NO → Pivot or kill ──────────────►│
│ Update canvas, re-enter │
│ │
├── YES → Next assumption ───────────►│
│ │
└── ALL VALIDATED → EXIT ─────────────┘Max iterations: 5 per assumption. If an assumption cannot be validated in 5 cycles, kill the idea or pivot the fundamental approach.
Step 1: REFLECT — Identify the Riskiest Assumption
List all assumptions the business model depends on. Rank by:
- Impact if wrong: would this kill the business? (High/Medium/Low)
- Uncertainty: how confident are we? (Guess/Belief/Tested)
Pick the assumption that is High-impact AND Guess/Belief. This is what you test first.
Common assumption categories:
- Problem assumption: "This problem exists and is painful enough to pay to solve"
- Solution assumption: "Our solution actually solves this problem"
- Pricing assumption: "They will pay $X for this"
- Channel assumption: "We can reach them through [channel]"
- Retention assumption: "They will keep using this after the first time"
Step 2: HYPOTHESIZE — Write a Testable XYZ Hypothesis
Format (Savoia's Pretotyping):
"At least X% of [target audience] will [desired action] if [condition/offering]"
Rules:
- X must be a specific number, not "some" or "many"
- Target audience must be concrete, not "developers" but "DevOps engineers who use Terraform"
- Desired action must be behavioral (click, sign up, pay), not attitudinal (say they like it)
- Set the threshold BEFORE running the experiment, not after
Also set fail conditions: what result would KILL this hypothesis? Write it down. If you can't define failure, you can't learn.
Step 3: EXPERIMENT — Run the Cheapest Possible Test
Experiment types (ordered by cost, cheapest first):
| Type | What | Time | Cost | Evidence Strength |
| Fake Door | Landing page with signup/buy button, no product behind it | 2 hours | $0 | Medium (interest, not commitment) |
| Concierge | Manually deliver the service to 3-5 people | 1-3 days | $0 | High (real usage data) |
| Wizard of Oz | Users think it's automated, but you do it manually behind the scenes | 3-5 days | $0 | High (real behavior) |
| Pre-sell | Take actual payments before the product exists | 1 day | $0 | Highest (money moved) |
| Smoke Test | Ads/posts pointing to a signup page, measure conversion | 1 day | $0-50 | Medium (intent, not usage) |
Rules:
- Always prefer skin-in-the-game data (money, time invested) over opinions (surveys, "I would use this")
- "Would you use this?" is worthless. "Here's the payment page, buy now" is data.
- If an experiment takes more than 1 week, it's too expensive. Simplify.
- Search the web for existing data before running your own experiment (someone may have already validated this)
Step 4: LEARN — Evaluate Against Threshold
Compare results to your XYZ hypothesis threshold:
| Result | Action |
| Exceeded threshold | Assumption validated. Move to next riskiest assumption. |
| Close to threshold (within 20%) | Iterate: adjust offering, pricing, or messaging. Re-run experiment. |
| Far below threshold | Assumption invalidated. Decide: pivot or kill. |
Pivot options (Steve Blank):
- Zoom-in pivot: one feature of the product becomes the whole product
- Zoom-out pivot: the whole product becomes one feature of a larger product
- Customer segment pivot: same product, different audience
- Customer need pivot: same audience, different problem
- Channel pivot: same product, different distribution channel
- Revenue model pivot: same product, different pricing/monetization
Kill criteria: if 3+ pivots on the same core idea all fail, kill it entirely. Start fresh with a new idea through biz-think.
Step 5: UPDATE — Revise the Lean Canvas
After each cycle, update these in auto memory (memory/validation_log.md):
Experiment: hypothesis, method, result, date, learningAssumptionStatus: which assumptions are now Validated/Invalidated/UntestedLeanCanvas: updated customer segment, problem, solution, channels, revenue based on learningsPivotHistory: if pivoted, record what changed and why
Exit Conditions
Exit to development (invoke pre-code):
- Problem assumption validated (people have this pain and will pay)
- Solution assumption validated (your approach solves it)
- At least 1 person has paid or committed to pay (pre-sale, LOI, deposit)
biz-thinkacid test can now be completed in one sentence
Exit by killing:
- 3+ pivots failed on the same core idea
- No behavioral evidence of willingness to pay after 3 experiment cycles
- Store the kill decision and learnings in auto memory (
memory/validation_log.md)
Do NOT exit because you're tired of iterating. Exit only when evidence supports the decision.
Macro Stages (Running Lean Traction Roadmap)
Track which stage you're in:
| Stage | Goal | How You Know You're Done |
| 1. Problem/Solution Fit | Validate the problem is real and your solution concept resonates | 5+ people describe the problem unprompted; solution demo gets "when can I use this?" |
| 2. Product/Market Fit | Validate people will pay and keep using it | Repeatable acquisition, activation rate >40%, monthly churn <5% |
| 3. Scale | Grow the validated model | Not your concern until stages 1-2 are done |
You are almost certainly at Stage 1. Do not skip to Stage 2 thinking.
Next Steps
Report to user: "Validation [PASS/FAIL]. Assumption: [which one]. Evidence: [what we found]"
Suggested next steps (user decides):
- All validated → "Run brand-build, then work-breakdown"
- Kill criteria met → "Start fresh with biz-think"
- Need experiment → "Run copy-craft for landing page"
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