SKILLEMALL.ai

BB x402-layer

This skill should be used when the user asks to "create x402 endpoint", "deploy monetized API", "pay for API with USDC", "check x402 credits", "consume API credits", "list endpoint on marketplace", "buy API credits", "topup endpoint", "browse x402 marketplace", "set up webhook", "receive payment notifications", "manage endpoint webhook", use "Coinbase Agentic Wallet (AWAL)", or manage x402 Singularity Layer operations on Base or Solana networks.

modbender/skill-library-mcp Agent Skills author: modbender MIT 25 files body ≈ 3 455 tokens Open the sourcegithub.com analyzed 2 d ago

This skill should be used when the user asks to "create x402 endpoint", "deploy monetized API", "pay for API with USDC", "check x402 credits", "consume API…

As a process B 69/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorGitHubCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
83
Quality 40%
79
Run on models
none yet
Process rating
B
69/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Inputs and preconditions w 11
30
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.

Broad scope 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 skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 13

    ✓ No critical or high findings

    Medium and low: 13
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Read Write Edit Bash WebFetch
    • low Secrets in code secret-high-entropy-token references/pay-per-request.md:41
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "payTo": "0xCD…275",
      quoted
    • low Secrets in code secret-high-entropy-token references/pay-per-request.md:52
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "payTo": "3rcd…qCx",
      quoted
    • low Secrets in code secret-high-entropy-token references/pay-per-request.md:53
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "asset": "EPjF…t1v",
      quoted
    • low Secrets in code secret-high-entropy-token references/pay-per-request.md:55
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "feePayer": "BENr…9SP"
      quoted
    • low Secrets in code secret-high-entropy-token references/pay-per-request.md:86
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "verifyingContract": "0x83…913"
      quoted
    • low Secrets in code secret-high-entropy-token references/payment-signing.md:15
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "verifyingContract": "0x83…913"
      quoted
    • low Risky intent intent-wallet-secrets scripts/consume_product.py:17
      Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target (quoted — discussed, not commanded)
      PRIVATE_KEY - Your EVM wallet private key (Base network)
      quoted
    • low Secrets in code secret-high-entropy-token scripts/consume_product.py:37
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      USDC_ADDRESS = "0x83…913"
      quoted
    • low Secrets in code secret-high-entropy-token scripts/solana_signing.py:124
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      token_program_id = Pubkey.from_string("Toke…5DA")
      quoted
    • low Secrets in code secret-high-entropy-token scripts/solana_signing.py:125
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      ata_program_id = Pubkey.from_string("ATok…knL")
      quoted
    • low Secrets in code secret-high-entropy-token scripts/solana_signing.py:126
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      usdc_mint_default = "EPjF…t1v"
      quoted
    • low Secrets in code secret-high-entropy-token scripts/wallet_signing.py:19
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      USDC_ADDRESS = "0x83…913"
      quoted

    Files scanned: 25. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 69/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 13 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 26 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3455 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -216 emoji in the instructions: noise for the model
    • -45 reference files, but SKILL.md never points to them: the model will not open them
    • -34 of 17 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 13 example trigger phrases
    • +3Description length 449: enough signal without eating the budget
    • +4Structure: 35 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (23 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.