Conciseness

The body is lean and command-driven — a dependency table, one-time whisper weight setup, and commented bash blocks — with no explanations of concepts Claude already knows. It is not 5 because of minor duplication that could be trimmed: the DB path appears both in the 前置环境 table and again in 注意, and MoneyPrinterTurbo reuse is restated across 任务目标 and 能力包含.

Actionability

Both workflows get concrete, flag-level commands (e.g. 'python kb_to_mpt.py --project-id <PID> --dry-run', 'python transcribe_fw.py ... --model small --lang zh') that are close to copy-paste ready. It falls short of 5 due to gaps: the four referenced Python scripts are not present in the bundle, whisper weights require manual placement with no command, and no concrete example values (e.g. a real project-id) are given.

Workflow Clarity

Both A and B flows are clearly sequenced with numbered, commented steps plus a full pipeline diagram, and the batch generation path includes an explicit validation checkpoint ('--dry-run 先看文案'), so the batch-operation cap does not apply. It is not 5 because there is no post-generation verification (e.g. checking the MPT API response) and no error-recovery feedback loop for the batch render or the DB ingest.

Progressive Disclosure

The body is well organized into purpose, capabilities, triggers, prerequisites, and two worked procedures — appropriate for a single-file skill of this length. It is not 5 because four scripts (kb_to_mpt.py, transcribe_fw.py, build_naval_cards.py, ingest_video_material.py) are named without paths or links and none of them exist in the bundle (no scripts/ directory), leaving navigation to the skill's actual artifacts broken.

Specificity

The description lists multiple concrete actions with named tooling — '把 knowledge_cards（蓝/绿/红卡）批量生成书摘/知识类短视频（复用 MoneyPrinterTurbo）' and '提供本地 faster-whisper 转写桥，把任意视频转文字入库成为脚本源' — covering both pipeline directions comprehensively for the skill's scope. It matches the anchor 'Lists multiple specific concrete actions; comprehensive coverage' and is not score 4, since no meaningful capability of the skill is left unmentioned.

Completeness

It explicitly answers both questions: a detailed 'what' (batch video generation from knowledge cards plus a transcription bridge into the knowledge base) and an explicit '触发：' clause with concrete trigger phrases. This matches the score-5 anchor 'Clearly and explicitly answers both what AND when with concrete trigger phrases'; score 4 would require the 'when' to be less explicit, which it is not.

Trigger Term Quality

It includes three natural quoted trigger phrases users would actually say ('把书/知识库做成视频', '批量产出书摘视频', '把视频转写进知识库') covering both use cases. It falls short of the score-5 anchor because common variations and synonyms are missing (e.g. '视频转文字', '下载字幕入库', '知识类视频'), but it is clearly above 'a few natural terms missing' being absent, so 4 fits best.

Distinctiveness Conflict Risk

The description occupies a clear niche — knowledge-base ↔ short-video pipeline built on MoneyPrinterTurbo and faster-whisper — with trigger phrases tied specifically to that niche (knowledge base to video, video to knowledge base), giving minimal conflict risk with generic video/transcription skills. It is not score 4 because the named tools and knowledge-base framing make overlap with any closely related skill unlikely.