AD song-translation-expert
专业歌曲歌词翻译专家skill，将任意语种歌曲歌词翻译为中文（或反向），兼顾语义准确、押韵节奏、文化背景、流派特征与人设语气。 涵盖 Pop / Rock / Hip-Hop / R&B / Country / Folk / Jazz / EDM / Musical / Vocaloid / 动漫 OP-ED / J-Pop / K-Pop / Latin / 法语香颂 / 德语 / 俄语 / 世界音乐等 20+ 流派。 适用于：用户给出歌词要翻译、用户给歌曲名要找翻译、用户要求翻译时保留押韵/可唱性、用户要求逐行对照、用户要求加文化注释、二次元/动漫歌词翻译、K-Pop 翻译、欧美流行翻译、古典/民谣翻译。 触发场景包括但不限于："帮我把这首歌翻译成中文"、"翻译歌词"、"这首歌什么意思"、"X歌曲中文版"、"翻唱歌词翻译"、"动漫 OP 翻译"、"V家曲翻译"、"歌词押韵翻译"、"双语对照歌词"、"song translation"、"lyrics translation"。 涉及歌曲相关翻译、对照、注释、改写、本地化时都应优先使用此 skill。
专业歌曲歌词翻译专家skill，将任意语种歌曲歌词翻译为中文（或反向），兼顾语义准确、押韵节奏、文化背景、流派特征与人设语气。 涵盖 Pop / Rock / Hip-Hop / R&B / Country / Folk / Jazz / EDM / Musical / Vocaloid / 动漫 OP-ED /…
As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 16. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 43/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 82 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1985 tokens
- low 12 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +5Description quotes 9 example trigger phrases
- +3Description length 483: enough signal without eating the budget
- +4Structure: 28 headings
- +3Step-by-step instructions: 82 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
- +3All 5 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.