SKILLEMALL.ai

AB cross-chain-arbitrage

Find and execute cross-chain arbitrage opportunities. Scans prices across all chains, evaluates profitability after all costs (gas, bridge fees, slippage), assesses risk, and executes if profitable. Uses ERC-7683 for cross-chain settlement. Supports scan-only mode for research without execution.

ClawHub Agent Skills author: wpank v0.1.0 3 files body ≈ 5 043 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 77/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
B
77/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5043 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 77/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 5043 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 23 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place

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
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 296: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 23 items
  • +3Output format is stated explicitly
  • +4Has examples (13 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
The skill is a coherent DeFi arbitrage workflow, but it deserves review because it can move wallet funds through cross-chain trades without clear default spending limits or wallet boundaries.
LLM: suspicious (medium) · VirusTotal: benign · 28 May 2026