The body is mostly substantive domain knowledge rather than generic concepts Claude already knows, but patterns are restated across 'Core Concepts' and 'Detailed Topics' and some attention-mechanic exposition could be tightened, fitting the 'mostly efficient but could be tightened' anchor.

Provides concrete thresholds (4K, 70%, 8K-16K tokens), a named four-bucket mitigation framework with use-conditions, worked examples, and a real reference script (degradation_detector.py), matching the 'specific examples, copy-paste ready' anchor.

Sequenced detection-to-recovery flows (e.g., poisoning circuit-breaker steps 1-4) and a pattern-keyed mitigation framework give clear sequencing; the diagnostic nature does not require destructive-operation validation checkpoints.

SKILL.md is a well-organized overview with a single one-level-deep reference (patterns.md) and a script (degradation_detector.py), both clearly signaled with 'Read when' navigation guidance, matching the 'clear overview with well-signaled one-level references' anchor.

Lists multiple concrete actions ('diagnosing and mitigating') and specific failure modes (lost-in-middle, poisoning, clash, confusion, attention-pattern issues), matching the 'lists multiple specific concrete actions' anchor.

Explicitly answers what ('diagnosing and mitigating context degradation') and when via the 'This skill should be used for...' trigger clause, satisfying the both-what-and-when anchor.

Includes some natural user phrases like 'agent performance degradation' and 'lost-in-middle failures,' but several terms ('context clash,' 'attention-pattern issues') are technical jargon a user would not naturally say, missing common variations.

Targets a clear niche (specific named degradation patterns) with distinct triggers unlikely to fire for adjacent skills, matching the 'clear niche with distinct triggers' anchor.