event-contract-design
Event Contract Design
Coverage
Design asynchronous event contracts for producers and consumers. Covers event envelope, schema, event type, topic/channel naming, producer ownership, consumer expectations, required and optional fields, idempotency keys, ordering, causation and correlation IDs, schema evolution, replay, dead-letter behavior, compatibility, observability, and machine-readable documentation such as AsyncAPI or CloudEvents-style metadata.
Philosophy
An event is a public promise once another consumer depends on it. If the payload, ordering, retry, or compatibility rules are implicit, every consumer invents its own interpretation and the event stream becomes shared folklore.
Do not confuse event discovery with event contracts. Discovery asks what happened in the domain. Contract design asks what exactly will be published, consumed, replayed, and evolved.
Method
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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