skills/brainstorm-diverge-converge/SKILL.md
Applies structured divergent-convergent thinking to generate many creative options, organize them into meaningful clusters, then systematically evaluate and narrow to the strongest choices. Balances creative exploration with disciplined decision-making. Use when exploring product ideas, solving open-ended problems, generating strategic alternatives, developing research questions, designing experiments, or when user mentions brainstorming, ideation, divergent thinking, generating options, or evaluating alternatives.
npx skillsauth add lyndonkl/claude brainstorm-diverge-convergeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Three phases: Diverge (generate many ideas without judgment), Cluster (group into themes), Converge (evaluate against criteria and select).
Quick Example:
# Problem: How to improve customer onboarding?
## Diverge (30 ideas)
- In-app video tutorials
- Interactive walkthroughs
- Email drip campaign
- Live webinar onboarding
- 1-on-1 concierge calls
- ... (25 more ideas)
## Cluster (6 themes)
1. **Self-serve content** (videos, docs, tooltips)
2. **Interactive guidance** (walkthroughs, checklists)
3. **Human touch** (calls, webinars, chat)
4. **Motivation** (gamification, progress tracking)
5. **Timing** (just-in-time help, preemptive)
6. **Social** (community, peer examples)
## Converge (Top 3)
1. Interactive walkthrough (high impact, medium effort) - 8.5/10
2. Email drip campaign (medium impact, low effort) - 8.0/10
3. Just-in-time tooltips (medium impact, low effort) - 7.5/10
Copy this checklist and track your progress:
Brainstorm Progress:
- [ ] Step 1: Gather requirements
- [ ] Step 2: Diverge (generate ideas)
- [ ] Step 3: Cluster (group themes)
- [ ] Step 4: Converge (evaluate and select)
- [ ] Step 5: Document and validate
Step 1: Gather requirements
Clarify topic/problem (what are you brainstorming?), goal (what decision will this inform?), constraints (must-haves, no-gos, boundaries), evaluation criteria (what makes an idea "good" - impact, feasibility, cost, speed, risk, alignment), target quantity (suggest 20-50 ideas), and rounds (single session or multiple rounds, default: 1).
Step 2: Diverge (generate ideas)
Generate 20-50 ideas without judgment or filtering. Suspend criticism (all ideas valid during divergence), aim for quantity and variety (different types, scales, approaches), and use creative prompts: "What if unlimited resources?", "What would competitor do?", "Simplest approach?", "Most ambitious?", "Unconventional alternatives?". Output: Numbered list of raw ideas. For simple topics → generate directly. For complex topics → Use resources/template.md for structured prompts.
Step 3: Cluster (group themes)
Organize ideas into 4-8 distinct clusters by identifying patterns, creating categories (mechanism, user/audience, timeline, effort, risk, strategic objective), naming clusters clearly, and checking coverage (distinct approaches). Fewer than 4 = not enough variety, more than 8 = too fragmented. Output: Ideas grouped under cluster labels.
Step 4: Converge (evaluate and select)
Define criteria (from step 1), score ideas on criteria (1-10 or Low/Med/High scale), rank by total/weighted score, select top 3-5 options, and document tradeoffs (why chosen, what deprioritized). Evaluation patterns: Impact/Effort matrix, weighted scoring, must-have filtering, pairwise comparison. See Common Patterns for domain-specific approaches.
Step 5: Document and validate
Create brainstorm-diverge-converge.md with: problem statement, diverge (full list), cluster (organized themes), converge (scored/ranked/selected), and next steps. Validate using resources/evaluators/rubric_brainstorm_diverge_converge.json: verify 20+ ideas with variety, distinct clusters, explicit criteria, consistent scoring, top selections clearly better, actionable next steps. Minimum standard: Score ≥ 3.5.
For product/feature ideation:
For problem-solving:
For research questions:
For strategic planning:
Do:
Don't:
resources/template.md - Structured prompts and techniques for diverge-cluster-convergeresources/evaluators/rubric_brainstorm_diverge_converge.jsonbrainstorm-diverge-converge.mdtesting
Cluster a conference's event records into a small set of coarse themes with finer sub-clusters, an explicit outlier bucket, and soft (multi-membership) affinities — using the hybrid embed-then-label pipeline (embed abstracts, reduce, density-cluster, then LLM-label the clusters) when embedding libraries are available, and an LLM-reasoned hierarchical fallback when they are not. Embeddings do the grouping; the LLM only names the groups. Conference-agnostic. Use when turning structured event records into a navigable theme map for preference elicitation and scheduling, when you need 6-8 reasonable themes rather than 20 muddy ones, or when overlapping talks must belong to more than one theme. Trigger keywords - theme clustering, cluster talks, embed then label, soft membership, outlier talks, conference themes, topic map.
development
Build a personal conference schedule as a constraint-optimization problem — hard constraints (no time overlap, room-to-room travel time, capacity/registration, the attendee's own must-attends and blackouts) plus a user-owned weighted objective trading interest against breadth, pacing (maximize contiguous free time), and serendipity. Surfaces unbreakable conflicts (two high-value overlapping talks the model cannot rank) as decisions for the human rather than silently picking, and reports what each choice traded away. Conference-agnostic. Use to turn a preference profile plus a theme map into a day-by-day plan, to resolve overlapping sessions, or to balance a packed vs paced schedule. Trigger keywords - schedule optimization, conference schedule, constraint optimization, overlapping talks, contiguous free time, conflict surfacing, packed vs paced.
development
Parse a heterogeneous conference program (markdown, HTML, PDF-derived text, or JSON) into normalized event records with per-field confidence scores and independent classification axes (topic, depth, format, prerequisites, recorded, capacity). Detects the program's format before extracting, treats every inferred field as uncertain (present vs inferred vs missing), and flags thin or missing abstracts so downstream enrichment can target them. Conference-agnostic. Use when ingesting a conference or event schedule into a structured store, normalizing a talk/session list, or extracting per-session metadata with calibrated confidence. Trigger keywords - program ingestion, parse schedule, session extraction, event records, conference program, talk metadata, per-field confidence.
development
Build a personalized preference profile from a small number of well-chosen, cluster-grounded questions instead of a long survey. Represents the person's interests as an uncertainty region over the theme map, picks the single highest-information-gain choice-based question (contrasting real talks from different clusters), balances exploiting known interests against exploring uncertain ones, deliberately injects outlier probes to fight selection bias, and stops as soon as the schedule would be stable. Also elicits the user-owned objective weights and hard constraints. Interactive — runs where it can actually ask the person. Conference-agnostic. Use to turn a theme map into a preference profile, to decide what to ask a conference attendee, or to elicit scheduling priorities. Trigger keywords - preference elicitation, ask few questions, information gain, choice-based questions, selection bias probe, objective weights, attendee preferences.