AD cryptowallet
Complete cryptocurrency wallet management for Web3, DeFi, and blockchain applications. Create and manage EVM (Ethereum, Polygon, BSC, Arbitrum, Optimism, Base, Avalanche) and Solana wallets with encrypted local storage. Query balances for native tokens (ETH, MATIC, BNB, SOL) and standard tokens (ERC20, SPL). Send transactions, interact with smart contracts, and manage multiple addresses across 12+ networks. Secure password-protected key storage with AES-256 encryption. Use for: (1) Creating new crypto wallets, (2) Importing existing wallets, (3) Checking token balances across chains, (4) Sending cryptocurrency and tokens, (5) Interacting with DeFi protocols and smart contracts, (6) Multi-chain portfolio management, (7) NFT transfers, (8) Blockchain development and testing. Keywords: crypto, cryptocurrency, wallet, blockchain, ethereum, solana, web3, defi, token, erc20, nft, smart contract, metamask alternative, hardware wallet, cold storage, hot wallet, blockchain wallet, digital wallet, bitcoin.
As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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
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low Secrets in code
secret-high-entropy-tokenSKILL.md:121High-entropy token-like string (may be an id, hash or a credential)python3 scripts/token_sender.py wallet recipient 100 --network polygon --token 0x27…174 --password "pwd"
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low Secrets in code
secret-high-entropy-tokenSKILL.md:124High-entropy token-like string (may be an id, hash or a credential)python3 scripts/token_sender.py wallet recipient 100 --network arbitrum --token 0xFF…CC8 --password "pwd"
Files scanned: 10. 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 48/100
- 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
- 30Running it twice. 5 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1659 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 10 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)
- +3Description length 1011: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -31 of 5 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 29 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.