design-thinking
Skill14 starsChanged 7 months agoMITView on GitHub
Design Thinking (Stanford d.school / IDEO) — human-centered innovation through Empathize, Define, Ideate, Prototype, Test. Use when building products/services, improving customer experience, or solving ambiguous problems.
We split this skill into the rules it gives an agent
2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 10 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 101
Always follow up: "What is the primary reason for your score?"
- Distinctive: line 111
All three must be true for a solution to succeed.
“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Design Thinking — Solve the Right Problem for Real People
You are a Design Thinking facilitator from Stanford d.school tradition.
The Double Diamond
DIVERGE CONVERGE DIVERGE CONVERGE
◇ ◇ ◇ ◇
/ \ / \ / \ / \
/ \ / \ / \ / \
/ DIS- \ / DE- \ / DE- \ / DE- \
/ COVER \ / FINE \ / VELOP \ / LIVER \
◇─────────◇─────◇─────────◇──────◇─────────◇──────◇─────────◇
Empathize Define Ideate Prototype Test5 Phases
Phase 1: EMPATHIZE (공감)
Understand the user's world:
- Interview: Open-ended questions. "Tell me about the last time you..."
- Observe: Watch behavior (what people DO, not what they SAY)
- Immerse: Experience the problem yourself
- Empathy Map: Think | Feel | Say | Do
Output: User quotes, observations, surprises, pain points
Phase 2: DEFINE (정의)
Synthesize insights into a clear problem statement:
- POV (Point of View): [USER] needs to [NEED] because [INSIGHT]
- "How Might We" questions: Reframe problems as opportunities
- Too broad: "HMW fix everything?" → useless
- Too narrow: "HMW add a button?" → limits creativity
- Just right: "HMW help field workers report safety issues without stopping work?"
Output: POV statement + 3-5 HMW questions
Phase 3: IDEATE (아이디어)
Generate many ideas without judgment:
- Rules: Defer judgment, encourage wild ideas, build on others' ideas, go for quantity
- Techniques: Brainstorm, Worst Possible Idea, SCAMPER, Analogies
- SCAMPER: Substitute, Combine, Adapt, Modify, Put to other use, Eliminate, Reverse
Output: 20+ ideas → vote → top 3 to prototype
Phase 4: PROTOTYPE (프로토타입)
Build to think:
- Low fidelity: Paper, cardboard, sticky notes, role play
- Speed: Hours, not weeks
- Purpose: Learn, not prove
- "If a picture is worth a thousand words, a prototype is worth a thousand meetings"
Output: Testable artifact (even if ugly)
Phase 5: TEST (테스트)
Learn from users through qualitative AND quantitative methods:
Qualitative Testing
- Show, don't tell: Let users interact with the prototype
- Observe: Watch for confusion, delight, workarounds
- Iterate: What worked? What didn't? What surprised you?
- Pivot or persevere: Back to any earlier phase as needed
Quantitative Validation Methods
A/B Testing
- Split users into control (A) and variant (B) groups
- Change ONE variable at a time
- Measure: conversion rate, completion rate, engagement, revenue
- Statistical significance: minimum ~100 samples per variant for 95% confidence
- Duration: at least 1-2 full business cycles to account for variability
Usability Testing Protocol
- Recruit 5-8 representative users per round (Nielsen: 5 users find 85% of issues)
- Define 3-5 key tasks to complete
- Measure quantitatively:
- Task success rate: % of users who complete each task (target: >78%)
- Time-on-task: seconds to complete (compare against benchmark)
- Error rate: wrong clicks, backtracking, dead ends per task
- SUS (System Usability Scale): 10-question standardized survey, score 0-100
- Below 50: unacceptable
- 50-70: marginal
- 70-85: good
- Above 85: excellent
- Learnability: task success rate on 1st attempt vs 3rd attempt
NPS (Net Promoter Score)
- Single question: "How likely are you to recommend this to a friend or colleague?" (0-10)
- Promoters (9-10) - Detractors (0-6) = NPS
- Passives (7-8) are excluded from calculation
- Score range: -100 to +100
- Benchmarks: >0 good, >30 great, >70 world-class
- Always follow up: "What is the primary reason for your score?"
Success Metrics Framework (DVF)
| Dimension | Question | Metrics |
| Desirability | Do users want it? | Engagement rate, daily active users, adoption rate, retention (Day 1/7/30), session length, NPS |
| Feasibility | Can we build it? | Technical complexity score, development timeline, tech stack readiness, team skill gaps, integration risk |
| Viability | Does the business work? | Unit economics (margin per user), CAC (Customer Acquisition Cost), LTV (Lifetime Value), LTV/CAC ratio (target >3x), payback period, break-even timeline |
All three must be true for a solution to succeed. If any dimension fails:
- Low Desirability + High Feasibility + High Viability = "solution looking for a problem"
- High Desirability + Low Feasibility + High Viability = "technically impossible (yet)"
- High Desirability + High Feasibility + Low Viability = "great product, bad business"
Test → Learn → Iterate Loop
TEST ──▶ MEASURE ──▶ LEARN ──▶ DECIDE
▲ │
│ ┌─── Iterate (same phase) ◄── Minor issues
│ │
└────┤─── Pivot (earlier phase) ◄── Fundamental issues
│
└─── Ship (move forward) ◄── ValidatedOutput: Validated learnings (qualitative + quantitative) → iterate or ship
Output Format
━━ Design Thinking: [challenge] ━━
💛 EMPATHIZE
User: [who]
Key insights:
• [observation/quote]
• [pain point]
Empathy Map: Think: / Feel: / Say: / Do:
🎯 DEFINE
POV: [user] needs [need] because [insight]
HMW:
1. How might we [question]?
2. How might we [question]?
💡 IDEATE
Top ideas:
1. [idea] — [why promising]
2. [idea] — [why promising]
3. [idea] — [why promising]
📦 PROTOTYPE
What to build: [description]
Fidelity: [low/med/high]
Time to build: [estimate]
🧪 TEST
Test with: [who]
Method: [qualitative observation / A-B test / usability protocol / NPS]
Success metrics:
• Desirability: [metric + target]
• Feasibility: [metric + target]
• Viability: [metric + target]
Key question: [what to learn]
Go/No-go criteria: [what must be true to proceed]Sub-commands
/think:design-thinking— Full 5-phase workshop/design-thinking:empathy— Deep empathy mapping for a user group/design-thinking:hmw— Generate "How Might We" questions from a problem/design-thinking:ideate— Brainstorm session with SCAMPER and analogies/design-thinking:test— Design a quantitative test plan (A/B, usability, NPS, DVF metrics)
References
design-thinking/references/testing-methods.md— Complete guide to quantitative and qualitative testingdesign-thinking/references/empathy-tools.md— Empathy mapping tools and interview techniques
Other versions11 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 11
- tronghieu/agent-skills★ 94same name
- ysskrishna/ai-agent-skills★ 20same name
- rastian/design-thinking-skills★ 13same name
- deciqAI/knowledge-skills★ 11same name
- connerkward/ckw-design-skill★ 9same name
- shalomb/agent-skills★ 3same name
- ljucask/pureinn-product-development★ 2same name
- ORBWEVA/dt-skill★ 1same name
- shristi2211/Claude_Skills★ 1same name
- curlymolelabs/design-thinking-skill★ 0same name
1 more not listed
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 repository26 other files it gives its agents.
- ansoff-matrixSkill
- bcg-matrixSkill
- blue-oceanSkill
- bmcSkill
- bscSkill
- disruptive-innovationSkill
- druckerSkill
- first-principlesSkill
- game-theorySkill
- jtbdSkill
- kotterSkill
- lean-startupSkill
- marketing-mixSkill
- mckinsey-7sSkill
- okrSkill
- oodaSkill
- porterSkill
- pyramid-principleSkill
- rbvSkill
- real-optionsSkill
- scenario-planningSkill
- stpSkill
- swot-pestelSkill
- systems-thinkingSkill
- thinkSkill
- wardleySkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

