| name | discovery-validation |
| description | Smart pre-build discovery that validates novel feature ideas before committing to a full PRD. Classifies objectives as common patterns (skip) or novel concepts (full validation with lean canvas, competitive scan, and risk assessment). |
| user-invokable | false |
Discovery Validation
Reference
- ID: S-PROD-05
- Category: Product
- Inputs: objective description, company.config.yaml, market context
- Outputs: Discovery Validation section (appended to PRD), or "skip" verdict for common patterns
- Used by: Product Agent
- Tool scripts: ./tools/artifact/validate.sh
Purpose
Not every feature needs discovery. Authentication, CRUD, and notifications are well-understood patterns -- just build them. But novel concepts (new business models, AI-powered interfaces, marketplace dynamics) carry real uncertainty and deserve lightweight validation before committing engineering time. This skill acts as a smart filter: it classifies the objective, skips discovery for common patterns, and runs a focused validation for novel concepts.
When to Use
- Before writing a PRD for any new feature or product
- When the solopreneur/PM is unsure if an idea has legs
- When the feature involves unfamiliar territory (new market, new UX paradigm, new business model)
- The Product Agent should invoke this skill as a first step before PRD generation
Discovery Validation Procedure
Step 1: Classify Objective (Smart Filter)
Determine whether this feature needs discovery by matching it against known patterns.
COMMON PATTERNS (skip discovery -- proceed directly to PRD)
These are well-understood, solved problems with established implementation patterns:
- Authentication / login / signup / password reset
- CRUD operations (create, read, update, delete for any entity)
- Notifications (email, push, in-app)
- File uploads / media management
- Search / filtering / sorting
- Pagination
- Settings / preferences pages
- Admin panels / dashboards
- Payment integration (Stripe, PayPal)
- User profiles / account management
- Comments / ratings / reviews
- Tags / categories / labels
- Export / import (CSV, PDF, etc.)
- Webhooks / integrations with known services
- Role-based access control (RBAC)
- Audit logging
- Internationalization (i18n)
If the objective matches a common pattern:
Output: "Discovery skipped -- [feature] matches common pattern: [category]. Proceeding to PRD."
Exit the skill. No further steps needed.
NOVEL CONCEPTS (full discovery required)
These involve genuine uncertainty about problem-solution fit:
- New business model or pricing paradigm
- New market segment the product has not served before
- New UX paradigm (AI-powered interface, voice UI, AR/VR)
- Marketplace or multi-sided platform dynamics
- AI/ML-powered features without precedent in the product
- Social/community features with network effects
- Features requiring new data sources or partnerships
- Anything the solopreneur describes as "I have never built something like this"
- Gamification or behavioral mechanics
- Content creation or collaboration tools with novel workflows
If the objective matches a novel concept, proceed to Step 2.
UNCERTAIN
If the objective does not clearly fit either category, ask the user:
"This feature sits between common and novel. Should I run discovery validation or proceed directly to PRD?"
Respect the user's decision.
Step 2: Lean Canvas (for NOVEL Concepts)
Produce a one-page lean canvas covering all nine boxes. Be specific -- generic answers defeat the purpose.
| Box | Prompt | Output |
|---|
| Problem | What are the top 3 problems this feature solves? | Specific, observable problems with evidence |
| Customer Segments | Who specifically has these problems? | Named persona(s) with context (role, company size, behavior) |
| Unique Value Proposition | Single clear compelling message | One sentence that would make the target persona stop scrolling |
| Solution | Top 3 features that address the problems | Concrete capabilities, not abstract descriptions |
| Channels | How will users discover this feature? | Specific channels (in-app prompt, email campaign, blog post, word-of-mouth) |
| Revenue Streams | How does this feature contribute to revenue? | Direct (new pricing tier, add-on) or indirect (retention, upsell trigger) |
| Cost Structure | What are the build + ongoing costs? | Engineering time estimate, infrastructure costs, third-party service costs |
| Key Metrics | What numbers prove this works? | 2-4 specific metrics with target values |
| Unfair Advantage | What makes this defensible? | Data, network effects, domain expertise, integrations, brand |
Step 3: Competitive Quick-Scan
Identify 3-5 closest alternatives and analyze them:
For each alternative:
- Name: Product or feature name
- How they solve the same problem: Specific approach, not vague description
- Pricing: Free, freemium, paid (with price point if known)
- Key differentiator: What they do better than others
Gap Analysis: What is missing from existing solutions? What do users complain about? Where is there whitespace?
Positioning: How will our approach be different or better? What trade-offs are we making? Why would someone switch from an existing solution?
Use WebSearch to find current competitors, recent reviews, and user complaints if needed. Do not fabricate competitor information -- if data is unavailable, state that explicitly.
Step 4: Risk Assessment
Riskiest Assumption
Identify the ONE thing that, if wrong, kills this idea. Be specific:
- Bad: "Users might not want this"
- Good: "Freelance designers earning $50-100K/year will pay $29/month for AI-generated client proposals because they currently spend 5+ hours per proposal"
Validation Approach
How to test the riskiest assumption cheaply, before building:
- Landing page with email capture (test demand)
- Concierge MVP (manual delivery of the value proposition)
- Survey of target persona (test willingness to pay)
- Wizard-of-Oz prototype (fake the backend, real the frontend)
- Competitor review mining (do users complain about the gap we would fill?)
Problem Validation Questions
| Question | How to Answer |
|---|
| Who has this problem? | Specific persona with demographics and behavior |
| How painful is it? (1-10 scale) | Evidence-based: time wasted, money lost, frustration signals |
| How are they solving it today? | Current workarounds, tools, manual processes |
| Will they pay for a better solution? | Willingness-to-pay signals: existing spend, stated intent, market comps |
Go/No-Go Recommendation
Based on the lean canvas, competitive scan, and risk assessment, provide one of three recommendations:
- Proceed to PRD: Evidence supports building this. Riskiest assumption is testable and the upside justifies the cost.
- Validate first: The idea has potential but the riskiest assumption is untested. Run the validation approach before committing to a PRD.
- Reconsider: Multiple red flags -- strong competition with no clear differentiator, unclear demand, or high cost with uncertain return.
Include a clear rationale for the recommendation (2-3 sentences).
Step 5: Output
Append a "Discovery Validation" section to the PRD (this is NOT a separate artifact -- it lives within the PRD):
## Discovery Validation
**Classification**: NOVEL -- [reason why this needed discovery]
**Lean Canvas**: [summary of the 9 boxes, or "See full canvas above"]
**Competitive Landscape**: [3-5 alternatives with gap analysis summary]
**Riskiest Assumption**: [the one specific thing that could kill this]
**Validation Status**: Validated / Needs Testing / Risky
**Recommendation**: Proceed to PRD / Validate first / Reconsider
**Rationale**: [2-3 sentences explaining the recommendation]
If discovery was skipped (common pattern), the PRD should include a brief note:
## Discovery Validation
**Classification**: COMMON PATTERN -- [category name]
**Discovery**: Skipped. This is a well-understood pattern with established implementation approaches.
Quality Checklist
