| name | validation-planner |
| description | Converts a chosen opportunity into a fast, falsifiable validation plan with numeric targets, success criteria, and kill thresholds. Use when a user has a selected opportunity, best bet, offer, or product wedge and needs to test demand before building or scaling. |
| compatibility | Works best when the input already includes a chosen path, user constraints, and some idea of target buyers. |
| metadata | {"author":"opencode","version":"0.1"} |
Validation Planner
Overview
This skill turns a chosen opportunity into a real demand test. The goal is not
to produce activity. The goal is to create a short validation plan with numeric
targets that can prove, narrow, or kill the idea quickly.
The plan should focus on the single biggest unknown, not on validating
everything at once.
Load references/experiment-patterns.md when selecting the right validation
motion. Load references/validation-metrics.md when defining thresholds.
When to use
- When a user already has a best bet or chosen opportunity
- When an idea needs validation before building, scaling, or quitting a path
- When a service-first, audience-first, or product-first wedge needs concrete
testing steps
Do NOT use when:
- The user still needs help choosing the opportunity itself
- The problem is purely implementation and demand is already proven
Workflow
1. Identify the real unknowns
Name the key risks behind the idea, such as:
- demand risk
- buyer-access risk
- willingness-to-pay risk
- workflow-repeatability risk
- legal-scope risk
Then choose the single biggest unknown. Name it explicitly and explain why
it matters more than the others right now.
2. Choose the right validation motion
Pick a test that matches the opportunity:
- Warm outreach and paid pilot
- Marketplace or directory test
- Audience pre-sell or waitlist
- Async product test
- Constraint-change plan for
no_go opportunities
Use the strongest available commitment signal the user can realistically ask
for, such as:
- deposit
- paid pilot
- pre-order
- signed implementation slot
- completed checkout
Do not stop at interviews, clicks, opens, or waitlist signups when a stronger
signal is feasible.
3. Define numeric success and failure criteria
Every plan should include numbers where possible:
- outreach count
- interview count
- conversion target
- payment target
- activation target
- stop or pivot threshold
Use decision-grade thresholds:
Briefly justify the numbers based on channel quality, audience size, price
point, access level, or sales cycle. Avoid fake precision.
4. Produce the plan
Return both:
- a readable validation plan
- a JSON block using
assets/validation-plan-template.json
Default sections:
Validation Thesis
Key Unknowns
7-Day Plan
Success Criteria
Kill Criteria
Structured Plan
Also include a brief Why Not The Lower-Signal Alternative explanation when
there is an obvious weaker motion, such as interviews instead of paid pilots.
Checklist
Examples
Example:
Input: Best bet is an HVAC missed-call recovery service with warm owner access.
Output: A 7-day plan with owner interview counts, pilot target counts, an offer
statement, and kill criteria tied to urgency and willingness to pay.
Common mistakes
| Mistake | Fix |
|---|
| Writing generic activity lists | Tie the plan to a specific unknown and numeric target |
| Validating everything at once | Choose the single biggest risk first |
| No stop condition | Add clear pivot or kill thresholds |
| Using weak signals when stronger ones are feasible | Ask for money, commitments, or defined next steps |
Quick reference
| Operation | How |
|---|
| Pick motion | Match the test to the opportunity and buyer access |
| Set targets | Use numeric thresholds from references/validation-metrics.md and justify them briefly |
| Format result | Human-readable plan plus JSON using assets/validation-plan-template.json |
Key principles
- Test the real risk — Validate the biggest uncertainty, not the easiest
activity.
- Numbers beat vibes — Use thresholds, counts, and time windows.
- Use the strongest available signal — If money or commitment can be asked
for, do not hide behind soft interest metrics.
- Kill fast when needed — A weak idea should be narrowed or stopped, not
endlessly studied.
Optimization Notes
- Preserve the user's requested output shape exactly and do not substitute generic advice for concrete artifacts.
- Include exact commands, code structures, protocol fields, tags, parameters, file paths, or deliverable sections when the task asks for them.
- Make safety gates explicit before irreversible, destructive, externally visible, or compliance-sensitive actions.
- For multi-step work, present steps in execution order and include validation or rollback checks where relevant.
- Avoid overfitting to a single eval example: express lessons as reusable rules, not as task-specific answers.