Conciseness

Nearly every line carries project-specific, non-inferable facts (file paths like 'plugins/extractor/trait.rs', exact trait/enum names, collision semantics, PyO3 0.29 behavior) with zero padding and no explanation of Rust or plugin concepts Claude already knows — matching the 'lean and efficient; every token earns its place' anchor.

Actionability

The registration snippet, feature-gating example, PostProcessor impl, and InternalDocumentExtractor skeleton are concrete and near copy-paste ready, backed by exact identifiers ('ProcessingStage', 'processing_stage()', 'get_document_extractor_registry()'). The impl bodies are elided with '{ /* ... */ }' and the skeleton is scaffolding rather than a complete example, so it sits just below 'fully executable; copy-paste ready'.

Workflow Clarity

Content is organized topically rather than as a numbered pipeline, but the registration flow (acquire registry → write lock → register, with cfg feature-gating), the Critical Rules checklist, and the testing requirements ('Test lifecycle, collision/replacement, concurrent access, and failure paths with test doubles') supply clear sequence and concrete checkpoints like 'ensure_initialized() before first extraction' and the alef(skip) guard. It falls short of 5 because the implement → register → test flow is never unified into one explicit ordered walkthrough with validate/retry guidance.

Progressive Disclosure

No bundle files exist, and the ~145-line body is well-sectioned with headers, tables, and code blocks that make navigation easy; cross-skill pointers ('see wasm-constraints', 'see alef-generated-bindings') are clearly signaled inline. The Alef-bridge and registry-invariants sections are self-contained enough that they could live in separate reference files, and the skill is over the 50-line simple-skill threshold, so this is 'good structure; minor organization gaps' rather than fully optimal split.

Specificity

The description lists several specific concrete targets — 'Xberg plugin traits, typed registries, priority collisions, lifecycle, native extractors, and Alef-generated Python plugin bridges' — but the verbs ('Design, implement, or diagnose') are generic and coverage of the plugin surface (e.g., post processors, registration, the binding-facing vs. in-crate distinction) has minor gaps, matching the 'several specific actions; minor gaps' anchor rather than comprehensive.

Completeness

Both parts are present: a clear 'what' (the enumerated plugin-system subjects) and an explicit 'when' ('Load for plugin-system work, not ordinary extractor parsing'), which avoids the missing-trigger cap of 3. The 'when' clause is brief and could name more concrete trigger phrases (e.g., 'when the user mentions plugins, registries, or priorities'), so it sits at 'both present; when could be more explicit' rather than the 5 anchor.

Trigger Term Quality

Terms like 'plugin', 'registry', 'extractor', 'priority', and 'plugin bridges' are natural phrases a user working on this codebase would say, giving good keyword coverage. A few natural variations and synonyms are missing (e.g., 'extend', 'add a new extractor', 'OCR backend', 'post processor'), keeping it below the comprehensive-with-synonyms anchor.

Distinctiveness Conflict Risk

The 'Xberg' qualifier plus the explicit negative boundary — 'not ordinary extractor parsing' — carves out a clear niche and actively prevents mis-triggering against an ordinary document-extraction skill, matching the 'clear niche with distinct triggers; minimal conflict risk' anchor.