Conciseness

Mostly efficient and dense with actionable specifics rather than concept explanation, but the very long 🟡/🔴 classification paragraphs and minor asides (扫描较慢耐心等、repeated read-only emphasis) could be trimmed.

Actionability

Provides copy-paste-ready commands (scan.py, server.py, build_report.py) and concrete field names (trash_paths, app_paths, tier_stats), but the full analysis JSON schema lives in build_report.py rather than inline — a minor gap.

Workflow Clarity

Clear four-step sequence (扫描→分级→报告→摘要) with explicit validation for destructive ops (three-whitelist security model, realpath + $HOME + token + confirm), a 铁律 checklist, and an 排障 feedback loop for error recovery.

Progressive Disclosure

System-specific data layouts are cleanly split into references/macos.md and references/windows.md (real, well-signaled, one level deep) with scripts separated out; the inline report-rendering detail (tier_stats parsing, pill/progress-bar rules) could partly move to a reference.

Specificity

Lists multiple concrete actions — 扫描整机磁盘占用、找出占空间大户、三级分类、给出可执行处置方案、生成交互式 HTML 报告、起本地服务一键删除 — giving comprehensive coverage of what the skill does.

Completeness

Clearly states both what the skill does and when to use it via an explicit 务必在以下场景使用 clause with concrete trigger phrases, fully answering both questions.

Trigger Term Quality

Enumerates a comprehensive set of natural user phrases (存储分析、磁盘满了、空间不够、清理空间、占空间、内存满了) plus English storage analysis / disk cleanup, covering synonyms and colloquial variants a user would actually say.

Distinctiveness Conflict Risk

Occupies a clear niche (read-only storage analysis with HTML report + one-click delete) with distinct triggers, and explicitly disambiguates RAM/运行内存 from storage to minimize conflict with activity-monitor style skills.