SKILLEMALL.ai

BC academic-literature-summary

精读并结构化总结中英文学术文献(期刊论文、学位论文、研究报告), 按固定学术结构输出中文精简总结。当用户要求"总结文献"、"精读文献"、 "文献综述"、"梳理文献"、"提炼文献要点"、"文献笔记"、"读论文"、 "概括论文"、"提取研究设计/方法/结果/讨论"、"文献结构分析"时触发。 支持从PDF/文本中提取内容,按固定结构(综述、假设、模型、研究详情、 讨论、结论)输出,保留引用格式,每节加emoji标识,忠于原文不编造。 同时支持将总结输出为Markdown文本或格式化的学术文档(DOCX/PDF)。

ClawHub Agent Skills author: xxx031211 v1.0.0 MIT-0 4 files body ≈ 1 124 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWordWriting and documentsResearchInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

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. 115 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1124 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -215 emoji in the instructions: noise for the model
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 256: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 115 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
The skill is mostly a text-only academic summarizer, but its optional DOCX/PDF mode tells the agent to create publisher-branded, journal-like documents and visuals that users could mistake for official or source-derived material.
LLM: suspicious (high) · VirusTotal: · 28 May 2026