BC academic-pdf-translation
将学术 PDF 翻译并重建为可读、可检索、可逐页验收的目标语言版本。用于全文翻译、旧译本修复、版式与行距审查、图表和截图文字本地化、语义忠实度复核、批量文献画像、源译对照图生成及 Zotero 收尾。简体中文流程已通过代表样本验证；繁体中文、日语、韩语及拉丁字母语言提供实验性配置，须先验收代表页。
将学术 PDF 翻译并重建为可读、可检索、可逐页验收的目标语言版本。用于全文翻译、旧译本修复、版式与行距审查、图表和截图文字本地化、语义忠实度复核、批量文献画像、源译对照图生成及 Zotero 收尾。简体中文流程已通过代表样本验证；繁体中文、日语、韩语及拉丁字母语言提供实验性配置，须先验收代表页。
As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.
Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.
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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Obfuscation
uni-zero-widthscripts/translation_truthfulness.py:123Zero-width / invisible characters (possible hidden text) (3 occurrences)for char in ("␀", "␀", "", "␀"):
Files scanned: 80. 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 52/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4016 tokens
- 100Steps. 57 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -324 of 55 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 149: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 57 items
- +4Has examples (36 code blocks)
- +4Reference files are cited in the instructions (12 of 13)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.