BF vocab-cards-lite
专业英语词汇闪卡生成器(精简版,包体仅68KB)。将「英文单词」批量生成「单词卡」「英文闪卡」「单词闪卡」: 从 JSON 单词数据一键生成黑白打印优化的主卡/副卡/百度百科二维码 PNG。 仅内置 IPA 音标裁剪字体,中英文使用系统字体(NotoSansCJK + DejaVu)。 触发场景:当用户提到「单词卡」「英文单词」「英文闪卡」「单词闪卡」「闪卡」「词汇卡」「flashcard」「vocab cards」 「背单词卡片」「打印单词卡」「批量生成单词卡」「英语卡片」「词卡 PNG」时使用。 适用于把单词表(含音标/词性/释义/搭配/例句/文化背景)批量转成可打印卡片图片的场景。 English: Generate printable black-and-white English vocabulary flashcard PNG images from JSON word lists, including main cards, optional side cards, and optional Baidu Baike QR-code cards, with a bundled IPA font plus system CJK and DejaVu fonts for clean multilingual rendering.
专业英语词汇闪卡生成器(精简版,包体仅68KB)。将「英文单词」批量生成「单词卡」「英文闪卡」「单词闪卡」: 从 JSON 单词数据一键生成黑白打印优化的主卡/副卡/百度百科二维码 PNG。 仅内置 IPA 音标裁剪字体,中英文使用系统字体(NotoSansCJK + DejaVu)。…
As a process F 35/100 · Will not run — References files that are not bundled: assets/fonts/
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 10. 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") - warning
missing-refreference to a missing file: assets/fonts/ - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName"
Process rating: all ten parameters 35/100
- 0Tools and files. 1 referenced file(s) missing: assets/fonts/
- 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
- 100Steps. 41 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1327 tokens
- 100Running it twice. No mutating operations
- 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
- +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
- +2Single-language instructions
- +3Description length 577: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.