Golden PDF Build Tester

The skill contains only a static PDF-document extract and does not instruct execution, network access, credential handling, or external side effects, so direct permission risk is limited. However, it omits data-flow disclosure, source attribution, sensitive-data handling, confirmation, and rollback guidance, so substantial points are deducted.

The SKILL.md, index, and manual are broadly consistent about pages and sections, and they expose code-block statistics. However, there are no test steps, input/output contract, abnormal-input handling, or diagnostic failure messages; the Python example is visibly truncated after x3, so the score remains low.

The stated use case is narrowly labeled as testing a PDF golden build, but trigger conditions, supported environments, non-fit boundaries, and an actionable workflow are absent. The supplied skill also provides no evidence of Chinese-language usability, so most adaptability points are deducted.

The skill uses a basic overview-to-reference structure, while repository context provides MIT licensing, version metadata, and CI/test maintenance signals. The selected skill itself lacks installation notes, changelog/versioning guidance, ownership/update path, FAQs, and limitation disclosure, and its name does not match the repository-level capability description, so points are deducted.

This is primarily a generated snapshot of a three-page PDF. It offers limited browsing value but no clear executable task, complete code, or directly usable output; its marginal benefit over reading the PDF directly is small, so the score is near the floor.

Page numbers, statistics, and reference paths provide limited traceability, and repository context includes test configuration and CI. Nevertheless, no executable evidence for this skill's key path is supplied; the example is truncated and the referenced image assets are not verifiable from the provided material, so the score is very low.