plugin-architecture-patterns

Design, implement, or diagnose Xberg plugin traits, typed registries, priority collisions, lifecycle, native extractors, and Alef-generated Python plugin bridges. Load for plugin-system work, not ordinary extractor parsing.

Quality

91%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

90%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An excellent, dense reference for plugin architecture: executable code, exact paths, and crisp rules with strong conciseness and actionability. Workflow clarity and progressive disclosure sit at 4 due to a missing explicit validation feedback loop and textual-only (non-linked) cross-skill references.

Suggestions

Add an explicit validate→fix→retry feedback loop for the registration/collision and binding-regen workflows (e.g. note that registration warns on collisions and how to resolve them before re-registering).

Convert textual cross-references like 'see wasm-constraints' and 'see alef-generated-bindings' into explicit file/path links so navigation is unambiguous.

For the Alef binding regen step, add a brief ordered sequence (change Alef config → regenerate → verify the bridge compiles) to make that destructive workflow's checkpoints explicit.

Dimension	Reasoning	Score
Conciseness	The body is lean and dense: tables, tight code snippets, and rule lists assume Claude's competence with Rust plugin internals, with no padding or explanation of basic concepts; every section earns its tokens.	5 / 5
Actionability	It provides copy-paste-ready Rust impl blocks (InternalDocumentExtractor, PostProcessor, registration with feature gating) plus exact file paths, trait signatures, and concrete rules, fully covering the common cases.	5 / 5
Workflow Clarity	Multi-step processes like registration and lifecycle are sequenced with concrete steps and explicit failure semantics ('Registration calls initialize() and rejects a plugin whose initialization fails'), but there is no explicit validate-then-retry feedback loop for the destructive/batch operations the skill touches.	4 / 5
Progressive Disclosure	Structure is well-organized with clearly signaled one-level-deep cross-references (e.g. 'see wasm-constraints', 'see alef-generated-bindings') and no bundle files to inline, but those references are textual hints rather than explicit navigable file links, leaving it just below a 5.	4 / 5
	Total	18 / 20 Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that concretely enumerates plugin-system capabilities and provides an explicit load/trigger clause with a negative boundary. The only minor gap is a slight lack of synonym/extension-style trigger terms.

Dimension	Reasoning	Score
Specificity	The description lists multiple concrete actions ('Design, implement, or diagnose') across a comprehensive set of plugin-system concerns (traits, typed registries, priority collisions, lifecycle, native extractors, Alef-generated Python bridges), matching the 'comprehensive coverage' anchor.	5 / 5
Completeness	It explicitly answers 'what' (design/implement/diagnose the listed plugin components) and 'when' via the explicit trigger clause 'Load for plugin-system work, not ordinary extractor parsing', satisfying both halves with concrete trigger phrases.	5 / 5
Trigger Term Quality	It surfaces natural plugin-system terms ('plugin traits', 'typed registries', 'priority collisions', 'lifecycle', 'Python plugin bridges') a user would plausibly say, but lacks common synonyms or file-extension-style variants, so it falls just below the comprehensive 5 anchor.	4 / 5
Distinctiveness Conflict Risk	The niche (Xberg plugin traits/registries/bridges) is highly specific and the negative trigger 'not ordinary extractor parsing' actively distinguishes it from a sibling extractor-parsing skill, giving it a clear niche with minimal conflict risk.	5 / 5
	Total	19 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: xberg-io/xberg
Path: .ai-rulez/skills/plugin-architecture-patterns/SKILL.md
Commit: 04336bd

Reviewed: 5 days ago

Table of Contents

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