skills/morphological-analysis-triz/SKILL.md
Explores solution spaces systematically through morphological analysis (parameter-option matrices) and resolves technical contradictions using TRIZ inventive principles to generate novel, non-obvious solutions. Use when exploring all feasible design alternatives before prototyping, resolving technical contradictions (speed vs precision, strength vs weight, cost vs quality), generating novel product configurations, finding inventive solutions to engineering problems, identifying patent opportunities, or when user mentions morphological analysis, Zwicky box, TRIZ, inventive principles, systematic innovation, or design space exploration.
npx skillsauth add lyndonkl/claude morphological-analysis-trizInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Morphological Analysis & TRIZ Progress:
- [ ] Step 1: Define problem and objectives
- [ ] Step 2: Choose method (MA, TRIZ, or both)
- [ ] Step 3: Build morphological box (if MA)
- [ ] Step 4: Identify contradictions (if TRIZ)
- [ ] Step 5: Apply TRIZ principles
- [ ] Step 6: Evaluate and select solutions
Step 1: Define problem and objectives
Clarify problem statement, key objectives, constraints (cost, size, time, materials), and success criteria.
Step 2: Choose method
Step 3: Build morphological box (if using MA)
See resources/template.md for structure.
Step 4: Identify contradictions (if using TRIZ)
State clearly:
See resources/template.md for 39 TRIZ parameters and contradiction matrix.
Step 5: Apply TRIZ principles
See resources/template.md for all 40 principles.
For advanced techniques, see resources/methodology.md.
Step 6: Evaluate and select
Morphological: Identify promising combinations, eliminate infeasible, score on objectives, select top 3-5
TRIZ: Assess contradiction resolution, check side effects, estimate difficulty, select most promising
Use resources/evaluators/rubric_morphological_analysis_triz.json for quality criteria.
Physical Products: Materials, power source, form factor, control interface, manufacturing method Software: Architecture, data storage, UI, deployment, authentication Services: Delivery channel, pricing model, timing, customization, support level Processes: Automation level, batch size, quality control, scheduling, location
| Improving ↑ | Worsens ↓ | Example TRIZ Principles | |-------------|-----------|------------------------| | Speed | Precision | Segmentation, Periodic action | | Strength | Weight | Anti-weight, Composite materials | | Reliability | Complexity | Segmentation, Beforehand cushioning | | Functionality | Ease of use | Segmentation, Universality | | Capacity | Size | Nesting, Another dimension |
Full principles list: See resources/template.md for all 40.
Morphological Analysis:
TRIZ:
General:
Resources:
resources/template.md - Morphological structure, TRIZ contradiction matrix, 40 principlesresources/methodology.md - Advanced TRIZ (trends of evolution, substance-field, ARIZ algorithm)resources/evaluators/rubric_morphological_analysis_triz.json - Quality criteriaOutput: morphological-analysis-triz.md with problem definition, morphological matrix (if used), contradictions, TRIZ principles applied, solution concepts, evaluation, selected solutions
Success Criteria:
Quick Decisions:
Common Mistakes:
Examples:
Morphological (Portable Speaker):
Power: Battery | Solar | Hybrid
Size: Pocket | Handheld | Tabletop
Audio: Mono | Stereo | Surround
Material: Plastic | Metal | Fabric
Control: Button | Touch | Voice | App
Result: 3×3×3×4×4 = 432 configs → Evaluate top 10
TRIZ (Electric Vehicle Range):
Contradiction: Increase range → worsens cost (battery expensive)
Principles: #6 (Universality - battery is structure), #35 (Parameter change - new chemistry)
Solution: Structural battery pack + high energy density cells
Combined:
Build morphological box for EV architecture → Top config has range/cost contradiction → Apply TRIZ Universality principle → Structural battery resolves both range and cost
For detailed principle explanations, contradiction matrix, advanced techniques (substance-field analysis, ARIZ, trends of evolution), and software/service adaptation, see resources/template.md and resources/methodology.md.
testing
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.