ideation
Ideation
Coverage
Ideation covers the techniques that produce many concept variants in response to a well-framed problem, then converge on a subset worth pursuing. The practice has two distinct halves and treats them as separable activities. Divergent techniques include Crazy 8s (eight sketches in eight minutes, popularized by Google Ventures' Design Sprint), brainwriting (silent written generation that bypasses dominant voices), SCAMPER (Substitute / Combine / Adapt / Modify / Put-to-another-use / Eliminate / Reverse — Bob Eberle's adaptation of Alex Osborn's checklist), worst-possible-idea (deliberately bad concepts to disinhibit and reveal hidden assumptions), headlines-from-the-future (write the press release for the launched product), and analogous inspiration (how do other domains solve adjacent problems).
Convergent techniques include dot voting (each participant gets N stickers to place on concepts they would invest in), the NUF test (Is it New, Useful, Feasible?), impact / effort 2×2 plotting, weighted decision matrices for multi-criteria selection, and assumption-testing prioritization (which concepts, if true, would teach the team the most). Convergent methods make the selection criteria explicit before voting begins, so the choice is defensible rather than political.
The skill includes the facilitation mechanics that keep the two halves separate: enforcing silence during divergent rounds so no idea is judged before it lands, time-boxing strictly so quantity is prioritized over polish, withholding feedback ("yes-and" rather than "yes-but"), and only opening evaluative discussion in the convergent phase. This separation is the single most-cited determinant of brainstorming productivity in the literature (going back to Osborn 1953, with the criticism / refinements from Diehl & Stroebe and others incorporated via brainwriting variants).
Philosophy
Ideation is built on a counterintuitive claim: that quantity precedes quality. The case is empirical and structural — judging an idea costs cognitive effort, and judgment running in parallel with generation suppresses generation. Teams that judge as they ideate produce fewer ideas, and the ideas they produce skew toward the safe middle of the distribution. By splitting the modes, divergent rounds produce a wider range, and convergent rounds can then prune intelligently because the field is large enough that pruning is meaningful.
The discipline is sceptical of "good enough" early ideas. The first three ideas a team generates are usually the obvious ones — the ones any competitor has also considered. The interesting ideas live in the second half of a forced-quantity round, where the obvious is exhausted and the team is pushed into less-trodden territory. Worst-possible-idea exercises serve the same function from the other direction: by deliberately violating norms, they expose which norms were holding the design back.
More from jacob-balslev/skill-graph
a11y
Use when building or reviewing interactive UI, forms, navigation, or dynamic content. Covers semantic HTML, keyboard access, focus management, labeling, state-change announcement, and reduced-motion / high-contrast preferences. Do NOT use for color-palette creation, visual branding, feedback-state staging, or prose reading-level accessibility - those belong to `visual-design-foundations`, `interaction-feedback`, and documentation respectively.
7intent-recognition
Use BEFORE any tool call that could modify state, touch sensitive targets, rewrite history, install dependencies, publish packages, or expose credentials/environment data. Classifies intent into Passive/Read, Reconnaissance, Modification, or Destructive/Irreversible using operation type plus target sensitivity, then runs Identify / Confirm / Verify before action. Do NOT use for deciding what code to write, executing already-classified work, reactive post-execution guardrails, or defining upstream governance policy.
6dependency-architecture
Use when designing or auditing dependency structure: package boundaries, runtime vs build dependencies, adapter layers, duplicate-purpose libraries, supply-chain risk, upgrade policy, lock-in, and dependency graph health. Do NOT use for choosing a major framework (use `framework-fit-analysis`), vulnerability-only review (use `owasp-security`), or routine refactoring without dependency boundary changes (use `refactor`).
6information-architecture
Use when structuring information for findability: navigation, page hierarchy, docs architecture, sitemap shape, labeling systems, wayfinding, and content grouping. Do NOT use for formal category-governance work (use `taxonomy-design`), responsive page composition (use `layout-composition`), component/token architecture (use `design-system-architecture`), or sentence-level UI text (use `microcopy`).
6design-thinking
Use when orchestrating a full human-centered design process across discovery, definition, ideation, prototyping, and testing — when uncertain which stage of the arc a team is in, when deciding whether to loop back, or when routing to the right stage-specific sibling skill. Do NOT use for single-stage execution (go directly to problem-framing, user-research, research-synthesis, journey-mapping, ideation, prototyping, or usability-testing) or for engineering domain discovery (use event-storming).
6knowledge-modeling
Use when deciding *which representation paradigm* fits a piece of domain knowledge — knowledge graph vs frames vs production rules vs semantic network vs concept map vs procedural ontology vs hybrid — when designing AI-agent context systems, building a knowledge base, structuring a skill or reference library, or planning a GraphRAG retrieval pipeline. Covers the seven paradigms with structure / best-for / weakness tables, the tacit-to-explicit knowledge acquisition pipeline (elicitation → articulation → formalization → validation → encoding), knowledge graph design principles (reify when needed, separate schema from instance, label precisely, bidirectional naming, minimal redundancy), the four knowledge-validation types (completeness / consistency / relevance / currency) plus expert walkthrough, the seven-phase knowledge lifecycle (Create / Validate / Publish / Use / Monitor / Update / Retire), the application to AI-agent systems (skills as frames, routing as rules, memory as graph), and a full GraphRAG section covering the five patterns (entity-anchored retrieval, relationship-aware context, path-based reasoning, subgraph summarization, hybrid vector+graph) with rules for when graph-grounded retrieval beats plain RAG. Do NOT use for the *human-readable* domain analysis layer (use `conceptual-modeling`), for the database / ER design layer (a logical-modeling skill), for pure classification hierarchies (a taxonomy skill), for formal ontology axioms (an ontology skill), or for the live skill-library tooling that consumes modeled knowledge (use `skill-infrastructure`).
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