SKILLEMALL.ai

BC freeland-x402-esim

Discover, compare, buy, and retrieve Freeland prepaid travel eSIMs through x402 with native USDC on Base. Use when an agent needs travel connectivity, an eSIM plan or quote, an x402 eSIM purchase, a live catalog lookup, purchase readiness, order recovery, or private owner delivery of eSIM installation credentials.

ClawHub Agent Skills author: elvismusli v1.0.1 MIT-0 3 files body ≈ 824 tokens Open the sourceclawhub.ai analyzed 3 d ago

Discover, compare, buy, and retrieve Freeland prepaid travel eSIMs through x402 with native USDC on Base.

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
94
Quality 40%
80
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Risky intent medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • medium Risky intent intent-wallet-secrets SKILL.md:28
      Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
      4. Sign the exact challenge with the user-owned payer wallet. Never request or expose a seed phrase or private key.
    • low Secrets in code secret-high-entropy-token SKILL.md:24
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - native Base USDC asset `0x83…913`;
      quoted

    Files scanned: 3. 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 61/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 4 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 824 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 315: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 27 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: clean
    This skill is a disclosed Freeland eSIM shopping and purchase workflow with payment safeguards and no hidden executable install behavior.
    LLM: benign (high) · VirusTotal: · 17 Aug 2026