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ERC-8004 identity, x402 payments, and arbitration protocol for autonomous agent commerce. The three rails for the machine economy.

modbender/skill-library-mcp Agent Skills author: modbender MIT 6 files body ≈ 5 216 tokens Open the sourcegithub.com↗ analyzed 3 d ago

ERC-8004 identity, x402 payments, and arbitration protocol for autonomous agent commerce.

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

IntegrationDockerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
77/100
safety, quality, tests
Safety 60%
91
Quality 40%
55
Run on models
none yet
Process rating
C
62/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 9

✓ No critical or high findings

Medium and low: 9
  • low Secrets in code secret-high-entropy-token capture.js:126
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    identityRegistry: '0x80…432',
    quoted
  • low Secrets in code secret-high-entropy-token capture.js:127
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    reputationRegistry: '0x80…b63',
    quoted
  • low Secrets in code secret-high-entropy-token capture.js:142
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    identityRegistry: '0x80…D9e',
    detector
  • low Secrets in code secret-high-entropy-token capture.js:143
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    reputationRegistry: '0x80…713',
    quoted
  • low Risky intent intent-wallet-secrets capture.js:3586
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target (quoted — discussed, not commanded)
    error: 'Wallet private key required for on-chain registration',
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:43
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…jgR+Mkmf+D189…ihQ==",
    detector
  • low Secrets in code secret-high-entropy-token SKILL.md:156
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Ethereum | `0x80…432` | Live |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:157
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Sepolia | `0x80…D9e` | Testnet |
    table
  • low Exfiltration net-credential-use SKILL.md:266
    Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
    curl -H "X-API-Key: $RECEIPTS_API_KEY" https://your-agent.fly.dev/list
    security skill

Files scanned: 6. 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")
  • warning body-long SKILL.md body ≈ 5216 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 62/100

  • 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
  • 30Running it twice. 15 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5216 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 78 steps
  • 100Consistency. Name and required fields are in place
  • 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

  • +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
  • -5TODO / placeholder text left in the skill
  • -215 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 130: enough signal without eating the budget
  • +4Structure: 70 headings
  • +3Step-by-step instructions: 78 items
  • +4Has examples (52 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.