diagnosis
Diagnosis
Coverage
The triage-first framework that classifies a software failure into a problem class and routes it to the right diagnostic technique before root-cause investigation begins. Names nine symptom classes — Logic Error, Runtime Crash, Data Integrity, Timing / Race, Performance, Configuration, Security, Integration, Tooling / Build / Script-path — and provides a classification decision tree that walks from "is there a stack trace?" to a single class. Specifies a universal evidence-collection protocol (exact error message, reproduction steps, last-known-good state, environment facts) and class-specific evidence checklists. Lays out the technique-selection matrix — stack-trace reading, data-flow tracing, git bisect, differential comparison, instrumentation, MRE isolation, profiling, boundary probing — with each technique's time cost, best-case class, and evidence prerequisite. Defines the diagnostic confidence ladder (level 0 Symptom → 1 Classified → 2 Localized → 3 Root Cause → 4 Verified Fix) with explicit "you can say / you cannot say" boundaries at each level and stuck-state checkpoints (5-min, 10-min, 15-min, oscillation). Names escalation criteria for switching approach, switching class, or escalating to a human. Covers three cross-domain patterns where multiple classes apply simultaneously: the Cascade (one root cause, many symptoms), the Coincidence (two unrelated bugs that look like one), the Environment Ghost (works in one environment, fails in another). Catalogues diagnostic anti-patterns and ships a structured diagnostic-session template.
Philosophy
Debugging fails most often not because the engineer lacks skill, but because the wrong methodology is applied to the problem class. A timing bug needs different tools than a data-integrity bug. A multi-tenant leak needs different thinking than a rendering glitch. The most expensive debugging mistake is spending 30 minutes applying scientific-method debugging to what is actually a configuration error discoverable in 2 minutes.
This skill is the triage nurse, not the surgeon. A nurse does not treat the patient — they take vital signs, route to cardiology or neurology, and escalate to the attending physician when criteria are met. Software diagnosis works the same way: collect evidence, classify the symptom, route to the right specialist technique, and pivot when convergence stalls. The 2–5 minute cost of triage is always smaller than the 30-minute cost of misdiagnosis. Skipping triage because "the cause is obvious" fails roughly 60% of the time on non-trivial bugs (confirmation bias) — even seasoned engineers benefit from making the classification step explicit.
1. The Diagnostic Triage Protocol
Before debugging, diagnose which kind of problem you have. The class determines the technique and the technique determines the time-to-fix.
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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