AC learning-cards
Spaced-repetition flashcard system backed by Feishu Bitable (multi-dimensional table). Create flashcards from any book or knowledge base, quiz the user interactively, track progress with 16 fields, and auto-schedule reviews using the 85% Rule. 基于飞书多维表格的间隔复习学习卡片系统。从任何书籍/知识体系生成学习卡片， 通过对话式问答练习，16 个字段追踪学习进度，85% 规则动态调整难度。 Use when / 使用场景: (1) User wants to study a book/course with flashcards / 用户想用卡片学习一本书或课程 (2) User says "继续学习", "来几张卡片", "continue studying", "quiz me" (3) User asks to create learning cards from a book or document / 用户要求从书籍或文档生成学习卡片 (4) User asks about learning progress, weak points, or review schedule / 查看学习进度、薄弱点、复习计划 (5) User mentions "学习卡片", "间隔复习", "spaced repetition", "flashcards"
As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
How to improve
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 58/100
- 0Result and completion. Does not say what the result is
- 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. 1 mutating operations with no state check
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1307 tokens
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
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 709: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.