Lean and efficient: no padding explaining what event sourcing is, assumes Claude's competence, and every section (When/How to use, worked example, anti-patterns, limitations, references) earns its place.

Provides fully executable Python test code in the worked example with real assertions (assert new_events == [...] , assert state_a == state_b) - copy-paste ready rather than pseudocode.

The 'How to use' section is a clearly sequenced 6-step process with validation intrinsic to each step (test assertions act as checkpoints), and the worked example shows the base-test-then-layer operational checks loop.

SKILL.md is a focused overview that points to one real, verified reference file (references/snapshot-versioning-projections.md), one level deep, clearly signaled with anchor text describing its contents; content is appropriately split.

Lists multiple concrete actions - 'given-events / when-command / then-events aggregate test, replay determinism', 'event-versioning + upcasting', 'snapshot equivalence', 'projection rebuild', 'retroactive event correction' - each naming a specific testable behavior.

Explicitly answers both what (the enumerated test types) and when via a clear 'Use when an event-sourced aggregate gains a new event type or a changed payload schema, when snapshots are introduced...' clause.

Good natural-term coverage: 'event-sourcing', 'aggregate', 'snapshot', 'projection', 'event log', 'payload schema', 'audit' are terms users would actually say when needing this skill.

A clear, narrow niche (event-sourced aggregate testing) with distinct triggers unlikely to fire for unrelated skills; uses third person ('Build'), no first/second person.