AD paper-reader
学术论文深度阅读技能。当用户提供 PDF 论文或论文文件路径时，自动执行全文翻译、 结构化讲解、图片解读和细节问答。适用场景：提供 PDF 文件路径、发送论文截图、 询问论文内容、请求解释某个术语或段落。 分析完成后可生成标准化摘要，方便后续生成 PPT（可选，非强制）。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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")
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 (paper-reader) differs from the folder (xiaosu-paper-reader)
- 100Tools and files. No external tools needed
- 100Steps. 51 steps
- 100Execution cost. Instruction body is 652 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 136: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 51 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: clean
This is a markdown-only academic paper-reading skill with a broad automatic workflow, but its behavior is disclosed and aligned with analyzing user-provided papers.
LLM: benign (high) · VirusTotal: · 28 May 2026