AD shiyi
拾遗 · 通用考试备考追踪 Skill。适用于任何考试——GRE、雅思、考研、注会、高考、期末…… 核心功能：识别错题截图 → 自由标签分类 → 词库积累复用 → 二刷提醒 → 导出 Excel。 触发关键词：做了题、错了、截图发来、导出错题、待二刷、记得、不记得、换考试。 图片消息直接触发识别。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ReferenceData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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: 12. 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 49/100
- 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
- 40Consistency. Frontmatter name (shiyi) differs from the folder (shiyi-study-tracker)
- 100Tools and files. No external tools needed
- 100Steps. 9 steps
- 100Execution cost. Instruction body is 767 tokens
- 100Running it twice. No mutating operations
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
- +1No license
- +2Single-language instructions
- +3Description length 149: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (4 code blocks)
- +3All 7 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: suspicious
This study-tracking skill is mostly coherent, but it stores sensitive screenshot-based study data persistently and has an export path that can be influenced by user text.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026