SKILLEMALL.ai

AC paper-reference-checker

This skill should be used when the user asks to "check paper citations", "verify references", "detect fake citations", "validate bibliography", "check if papers exist", "查文献真伪", "检查论文引用", "验证参考文献", "识别虚假引用", or uploads a PDF/Overleaf document and wants to verify whether the cited papers genuinely exist. Provides systematic verification of academic references against Google Scholar, CNKI, arXiv, and other academic databases to detect AI-hallucinated or fabricated citations.

ClawHub Agent Skills author: Ben Chen v1.2.1 MIT-0 7 files body ≈ 508 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

ReferenceLaTeXResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 508 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
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 477: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 6 items
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This citation-checking skill is instruction-only and appears to do what it says: verify user-provided academic references against public scholarly databases.
    LLM: benign (high) · VirusTotal: · 29 May 2026