SKILLEMALL.ai

BC x402lint

Conformance scanner and graded discovery directory for x402 sellers — lint an origin against 25 checks spanning the protocol surface, agent docs, and directory standing (x402scan / Bazaar / AgentCash), and get an A–F grade with per-check evidence and one-line fixes. Every scanned origin becomes a public directory project (browse the free directory / featured / per-project endpoints); a grade measures protocol conformance only and is NOT an endorsement. Free status, check-category summary, directory, and domain-control verification; paid full scan and cached report. Pay-per-call via x402 (USDC on Base); no accounts, no keys.

ClawHub Agent Skills author: Julius v1.0.0 MIT-0 2 files body ≈ 2 894 tokens Open the sourceclawhub.ai analyzed 2 d ago

Conformance scanner and graded discovery directory for x402 sellers — lint an origin against 25 checks spanning the protocol surface, agent docs, and…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
71
Run on models
none yet
Process rating
C
51/100
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

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

  1. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Risky intent intent-wallet-secrets skill-card.md:20
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    Risk: Optional paid MCP tools use a wallet private key and funded USDC on Base. <br>

Files scanned: 2. 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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 51/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 11 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2894 tokens
  • 100Running it twice. Mutating operations check current state

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 631: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 11 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
The skill is a transparent x402 conformance scanner guide with paid wallet-enabled options that are disclosed, but users should treat the optional wallet private key with care.
LLM: benign (high) · VirusTotal: · 26 Jul 2026