pattern-recognition
Pattern Recognition
Coverage
The methodology for identifying recurring structures across code, errors, board state, design systems, and domain data — then acting on them systematically rather than symptom-by-symptom. Names the six-step recognition loop (Observe → Cluster → Name → Codify → Detect → Prevent) with an optional Refine stage and the discipline at each stage. Catalogues code pattern classes (naming violations, duplication, anti-patterns, convention drift, missing guards, stale patterns) with detection methods and false-positive risks. Specifies the grep-based audit pattern as a six-step sequence (define → scan → count → sample → classify → triage) and the three-pass audit strategy (discovery → refinement → verification). Documents error-pattern clustering via normalize-then-hash extraction with ten error categories and severity-by-frequency triage rules. Names nine board-health patterns (stale in-progress, column overflow, WIP overflow, duplicate suspect, orphan in-progress, etc.) and the structural prevention each implies. Covers design pattern recognition (heading hierarchy contract violations, design token drift, triple-encoding requirement, component boundary violations) and domain-encoding patterns (null-vs-zero distinction, integer encoding for monetary amounts, magnitude-conversion at display boundary, source-rank trust hierarchy). Defines the eval-as-pattern-test pipeline and a 5-Whys ladder for root cause vs symptom analysis. Closes with pattern lifecycle states (Active / Fixed / Stale / Migrated), cross-session pattern persistence, a verification checklist, and six named drift traps (pareidolia, false clustering, stale patterns, over-abstraction, ignoring context, fixing at the wrong level).
Philosophy
Agents that operate symptom-by-symptom burn tokens without building leverage. An agent that recognizes patterns can propose systemic fixes, write automated detection rules, and prevent entire classes of bugs from recurring. This skill teaches the methodology — not just what to look for, but how to elevate a single finding into a durable detection and prevention mechanism.
The core discipline: require three instances before codifying a pattern. One is a bug. Two is a coincidence. Three is a pattern worth naming and automating. In a high-velocity agentic environment, manual review scales poorly — pattern recognition lets agents "see" the codebase as a system of rules rather than a collection of files. The premature codification of a pattern after one or two instances creates false rules that block valid code; the failure to codify after the third instance leaves the team to keep paying the same review cost on every future commit.