SKILLEMALL.ai

AC yunlv-cantonfair

Use when user needs to generate Canton Fair lead discovery strategies and outreach plans. Use when generating trade show customer development strategies. Use when creating personalized outreach content, product categories, booth information references. Use when user mentions "广交会", "展会获客策略", "摊位号", "展商开发", "展会客户开发策略", "采购商开发策略".

ClawHub Agent Skills author: WangM-A3 v1.1.0 MIT-0 8 files body ≈ 1 489 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

GeneratorSales and CRMInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
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

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

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "progressive"
    • note frontmatter-key unknown frontmatter key "triggers"

    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. 73 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1489 tokens
    • 100Running it twice. No mutating operations
    • low 14 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -227 emoji in the instructions: noise for the model
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 330: enough signal without eating the budget
    • +4Structure: 35 headings
    • +3Step-by-step instructions: 73 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This Canton Fair lead-generation skill is mostly purpose-aligned, but users should review it because it uses an external API and contact data while its data-flow and retention promises are inconsistent.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026