SKILLEMALL.ai

AC orderly-deposit-withdraw

Handle token deposits and withdrawals across chains, including allowance approval, vault interactions, and cross-chain operations

ClawHub Agent Skills author: Mario Reder v1.0.0 2 files body ≈ 4 560 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
84
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token SKILL.md:183
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "42161": "0xaf…831",
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:184
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "10": "0x0b…f85"
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:302
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      verifyingContract: '0x6F…203', // Mainnet Ledger
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:303
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      // verifyingContract: '0x18…bff' // Testnet Ledger
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:385
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "verifyingContract": "0x6F…203"
      quoted

    Files scanned: 2. 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 52/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4560 tokens
    • 100Steps. 41 steps
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • low 16 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 129: enough signal without eating the budget
    • +4Structure: 36 headings
    • +3Step-by-step instructions: 41 items
    • +4Has examples (19 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    This documentation-only skill matches its crypto deposit and withdrawal purpose, but its examples handle real asset movements with under-scoped safety controls.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026