Systems Lab

Agent skill

whitespace-finder

Systematic unmet-needs discovery engine that maps gaps between market demand and existing solutions with quantified opportunity scores.

slowingSelf-containedInstructions only659 words

Filed under Calls, demos and discovery.

From varunk130/ai-gtm-skill-library · 31 skills · 5 · pushed 2026-07-31

What it does when it runs

Systematic unmet-needs discovery engine that maps gaps between market demand and existing solutions with quantified opportunity scores. Use when: find opportunities, unmet needs, market gaps, opportunity discovery, what should we build, where is the whitespace.

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Ask about whitespace-finder

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git clone --depth 1 --filter=blob:none --sparse https://github.com/varunk130/ai-gtm-skill-library.git /tmp/ai-gtm-skill-library
git -C /tmp/ai-gtm-skill-library sparse-checkout set "gtm-skills/whitespace-finder"
mkdir -p ~/.claude/skills/whitespace-finder
cp -R "/tmp/ai-gtm-skill-library/gtm-skills/whitespace-finder/." ~/.claude/skills/whitespace-finder/

Picked up without a restart. A project skill of the same name is shadowed by your personal one. For one repository only, swap ~/.claude/skills for .claude/skills. Claude Code docs ↗

The folder is the same in every client that implements the format — 46 of them — so if yours is not above, only the destination changes.

Reproduced in full from varunk130/ai-gtm-skill-library/blob/90e878c73a8fbfd1cab864424ccf674fdc889157/gtm-skills/whitespace-finder/SKILL.md, which is licensed MIT (repository). 659 words, 11 headings.

Whitespace Finder (DEPTH Model)

Map the gap between what the market demands and what exists. Produces quantified, validated opportunity scores for product and GTM decisions.

When to Use

  • New product ideation
  • Feature prioritization against market need
  • Adjacent market exploration
  • Investment thesis validation
  • Pre-PRD opportunity validation

What You'll Need

Critical inputs (ask if not provided):

  • Market or product category to analyze
  • Target customer segment(s)
  • Known competitors (or ask me to research)

Nice-to-have:

  • Signal Radar output (if previously run)
  • JTBD Extractor output (if previously run)
  • Customer feedback or support ticket themes

Process

Step 1: Demand Evidence Collection

Audit demand across 6 evidence channels:

ChannelWhat to Look ForEvidence Quality
Community forums (Reddit, HN, Discourse)Problem-statement posts, workaround discussionsMedium -- shows real pain
Review mining (G2, Capterra, TrustRadius)1-3 star review complaint patterns, missing feature mentionsHigh -- verified buyers
Search demandVolume for problem queries vs. solution queries (gap = unmet need)High -- quantifiable
Support ticketsRecurring themes, feature requests, workaround patternsHigh -- your own customers
Analyst reportsProblem statements, unmet need callouts, market gaps citedHigh -- expert validation
Adjacent product requestsFeatures users ask for that cross product boundariesMedium -- shows expansion opportunities

For each channel, extract the top 5 unmet needs with supporting evidence.

Step 2: Gap Matrix Construction

Build a 2D matrix:

  • X-axis: Customer needs/jobs (from research or JTBD Extractor)
  • Y-axis: Existing solutions in market (products, workarounds, manual processes)

Rate each cell:

RatingMeaning
0Completely unaddressed -- no solution exists
1Poorly addressed -- solutions exist but are inadequate
2Adequately addressed -- good-enough solutions exist
3Well addressed -- strong solutions, hard to differentiate

Whitespace = cells rated 0-1 with strong demand evidence.

Step 3: DEPTH Scoring

Score each whitespace opportunity (1-10):

DimensionWhat It MeasuresScoring Guide
Demand EvidenceVolume and quality of signals indicating real demand1=anecdotal, 5=multiple sources, 10=overwhelming evidence
Existing SolutionsHow well current solutions address it (inverse)1=well solved, 5=partial solutions, 10=nothing exists
Pain IntensitySeverity of unmet need1=nice-to-have, 5=significant friction, 10=hair-on-fire problem
Total Addressable NeedSize of population with this unmet need1=tiny niche, 5=meaningful segment, 10=mass market
Hurdle AnalysisBarriers to entry (inverse -- high = low barriers)1=massive barriers, 5=moderate effort, 10=easy to enter

Opportunity Score = (D x 0.25) + (E x 0.20) + (P x 0.25) + (T x 0.15) + (H x 0.15)

Classification:

  • 7.5+ = Prime Opportunity (high confidence, prioritize)
  • 5.0-7.4 = Promising (validate further before committing)
  • Below 5.0 = Marginal (park unless strategic fit is strong)

Step 4: Opportunity Clustering

Group related whitespace opportunities into "opportunity zones" that could be addressed by a single product or feature set. Each zone gets:

  • Combined DEPTH score (weighted average of constituent opportunities)
  • Shared customer segment
  • Common technical requirements
  • Estimated effort to address

Output

Save to outputs/whitespace-[market]-[YYYY-MM-DD].md

Deliverables:

  1. Gap Matrix: Heat map of needs vs. solutions with whitespace cells highlighted
  2. Opportunity Scorecards: One per whitespace opportunity with DEPTH scores and evidence citations
  3. Opportunity Zones: Clustered opportunities showing which can be addressed together
  4. Validation Roadmap: Prioritized experiments to validate top opportunities (surveys, prototypes, landing page tests)

Chain Connections

  • Next skill: Run market-analyzer to size the opportunities you discovered
  • Also feeds: position-lock (validated opportunities become positioning targets), battle-scanner (whitespace informs differentiation angles)
  • Enhanced by: Run after signal-radar (signals point to where whitespace may exist)

Other skills for the same job

Different authors, same problem. Matched on the words in the skill name, across every library in the catalogue except this one.

Need help setting it up?

This page tells you what whitespace-finder does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.

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