SKILLEMALL.ai

BB Cross-border Product-Market Fit Validator

Validate product demand in any foreign market before investing in localization, hiring, or launch. Get assumption maps, low-cost experiments, evidence scorecards, and go/no-go decisions — install and run your first PMF test in under 30 seconds.

ClawHub Agent Skills author: haidong v1.0.2 MIT-0 6 files body ≈ 2 557 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

Validate product demand in any foreign market before investing in localization, hiring, or launch.

As a process B 66/100 · Nearly there — weak spots: failures and branches, consistency, running it twice

AnalyzerAI and agentsPeople and hiringtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
B
66/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 66/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (Cross-border Product-Market Fit Validator) differs from the folder (cb-product-market-fit-validator)
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 53 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Execution cost. Instruction body is 2557 tokens
    • 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 244: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 53 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    The skill is mostly a descriptive market-validation planner, but it includes a concrete Amazon review-acquisition tactic that could be non-compliant and should be reviewed before installation.
    LLM: suspicious (medium) · VirusTotal: · 16 Sept 2026