AC chinese-journal-paper
从项目代码仓库出发，自动扫描代码提取创新点，撰写符合中文核心/普刊规范的学术论文。核心能力：① 代码仓库扫描与技术创新点提炼 ② 参考文献格式占位（用户手动填充） ③ 生成完整论文（标题、摘要、关键词、引言、相关工作、方法、实验、结论）。触发词：论文、写论文、期刊论文、学术论文、核心期刊、普刊、中文论文、journal paper、帮我写论文、从代码写论文、项目写论文。当用户提到'论文'且上下文涉及代码或项目时，应优先使用此skill。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedurePersonal productivityInfrastructuretype 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: 5. 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") - note
frontmatter-keyunknown frontmatter key "triggers"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 73 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1622 tokens
- 100Running it twice. No mutating operations
- low 16 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 220: enough signal without eating the budget
- +4Structure: 28 headings
- +3Step-by-step instructions: 73 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: clean
This is a markdown-only Chinese academic paper drafting skill whose repository reading is disclosed and purpose-aligned, with no evidence of hidden execution or data exfiltration.
LLM: benign (high) · VirusTotal: · 29 May 2026