SKILLEMALL.ai

BC reference-checker

Exhaustively verify English and Chinese manuscript references before journal submission. Use when checking whether references are real, accurate, complete, traceable, and formatted consistently. Uses DOI/PubMed/Crossref/publisher checks for English/international references, and uses Chinese-title-first CNKI/Wanfang/VIP/official-source checks for Chinese references. DOI is optional for Chinese references and must not be required unless the target citation style explicitly requires it.

ClawHub Agent Skills author: Xiangjian Liu v1.0.2 MIT-0 3 files body ≈ 5 235 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 58/100 · Has gaps — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerInfrastructureResearchPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
C
58/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5235 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 58/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 16 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Failures and branches. 16 branches
  • 70Execution cost. Instruction body is 5235 tokens
  • 85Steps. 245 steps, 3 vague phrases
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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)
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 488: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 245 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This is a reference-checking instruction skill that asks the agent to verify academic citations using appropriate scholarly sources, with no hidden code or credential use found.
LLM: benign (high) · VirusTotal: · 3 Jun 2026