SKILLEMALL.ai

BD paper-check

专业的综合论文查重与检测 Skill:回答维普、万方、知网产品选择、检索范围、检测原理、报告指标、结果差异、引用规范、AIGC 和学术诚信问题;也能按用户意图调用现有用户端接口完成字符统计、上传、建单和查询,并返回原用户端浏览器地址。不需要 MCP、登录或 API Key。用户提到论文查重、论文检测、重复率、文字复制比、相似比、降重、AI率/AIGC、维普/VPCS、万方、知网/CNKI、字符数、报告解读、报告真假、报告验真、真伪查询、报告编号在哪里、验证码怎么填或官方验真入口时使用。

ClawHub Agent Skills author: zslzxy v3.2.0 MIT-0 54 files body ≈ 1 623 tokens Open the sourceclawhub.ai analyzed 2 d ago

专业的综合论文查重与检测 Skill:回答维普、万方、知网产品选择、检索范围、检测原理、报告指标、结果差异、引用规范、AIGC 和学术诚信问题;也能按用户意图调用现有用户端接口完成字符统计、上传、建单和查询,并返回原用户端浏览器地址。不需要 MCP、登录或 API…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationWordAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 53. 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 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1623 tokens
  • 100Running it twice. No mutating operations
  • low 10 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
  • -45 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 245: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: clean
This skill is a disclosed paper-checking helper that can upload user-provided manuscripts to fixed checking services and create unpaid orders, with clear limits against auto-payment, fake reports, and bypassing verification.
LLM: benign (high) · VirusTotal: · 29 Aug 2026