The description lists multiple specific concrete actions and concepts: building/reviewing Salsa databases, tracked functions, input/tracked/interned structs, query pipelines, accumulators, cancellation, durability, LSP integration, memory management, cycles, and production architecture. These are highly specific capabilities.

Clearly answers both 'what' (mental-model reset for Salsa incremental computation framework) and 'when' with an explicit 'Use when...' clause listing specific scenarios, plus a 'Triggers on' clause enumerating exact keywords. Both dimensions are thoroughly addressed.

Excellent coverage of natural trigger terms including specific Salsa macros (#[salsa::db], #[salsa::input], #[salsa::tracked], etc.), internal concepts (memoization, revisions, backdating, red-green algorithm), and configuration options (returns(ref), no_eq, lru, cycle_fn). A user working with Salsa would naturally use many of these exact terms.

Extremely distinctive — Salsa is a niche Rust framework, and the description includes highly specific macro names and internal concepts (e.g., #[salsa::tracked], red-green algorithm, backdating, WillExecute) that would not overlap with any other skill. Virtually zero conflict risk.

The skill is generally well-structured but includes some unnecessary content for Claude: the ASCII diagram, the 'Real-World Scale' section with detailed project stats, and the extensive 'Further Reading' links add bulk without proportional instructional value. The introductory paragraph explaining what Salsa is and naming projects that use it is somewhat redundant given the description already covers this.

The skill provides concrete, executable Rust code examples for every core concept — database setup, inputs, tracked functions, tracked structs, interned structs, and accumulators. The core loop example is copy-paste ready and clearly demonstrates the create-compute-mutate-recompute cycle.

The core loop (create inputs → compute → mutate → recompute) is clearly sequenced, but there are no validation checkpoints or error recovery steps. For a framework where design decisions about granularity and identity are described as 'the hardest part,' there's no guidance on how to verify correctness of those decisions or debug when incremental reuse isn't working as expected.

Excellent progressive disclosure structure: the main file provides a concise overview of each concept with inline code examples, then clearly signals deep-dive references via '→ Deep dive:' links and a well-organized navigation table mapping tasks to specific files. References are one level deep and clearly signaled.