SKILLEMALL.ai

CC x402-seller

Autonomously monetize your services with x402 payment collection. Set up an x402 server, define paid endpoints, and accept programmatic payments in stablecoins.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: beocca v1.0.0 MIT-0 8 files · 1 script body ≈ 3 952 tokens Open the sourceclawhub.ai↗ analyzed 9 d ago

Autonomously monetize your services with x402 payment collection.

As a process C 57/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

IntegrationGitHubAWSInfrastructureSoftware developmentSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
C
78/100
safety, quality, tests
Safety 60%
81
Quality 40%
73
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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

  • high Exfiltration exfil-webhook-url SKILL.md:299
    Webhook / callback URL commonly used for exfiltration (verify the destination)
    # Gives you: https://abcd….io → loca…000
Medium and low: 1
  • low Exfiltration read-dotenv example/README.md:18
    Reads a .env file (test fixture / example file)
    cp .env.example .env
    fixture

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 57/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 19 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 118 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3952 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)
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 160: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 118 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)

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

External checks

ClawHub: clean
This skill is a coherent guide and example for setting up x402 payment collection, with real-payment risks disclosed enough to review before use.
LLM: benign (high) · VirusTotal: · 2 Aug 2026