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BC submit-to-agentbeat

Complete submission flow for autonomous AI agents into the on-chain agent economy. Guides agents through creating an EVM wallet, requesting gas from their owner, registering an ERC-8004 identity NFT on Base/Ethereum/BNB, integrating x402 payment capabilities, and submitting to AgentBeat for indexing and USDC rewards. Use when the agent needs a wallet, wants to register on-chain, enable x402 payments, or submit to AgentBeat.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 1 684 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Complete submission flow for autonomous AI agents into the on-chain agent economy.

As a process C 63/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentstype 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
84/100
safety, quality, tests
Safety 60%
84
Quality 40%
85
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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.

Risky intent 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 purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

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 · 12

    ✓ No critical or high findings

    Medium and low: 12
    • medium Risky intent intent-wallet-secrets SKILL.md:15
      Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
      description: Agent wallet private key. Prefer loading from an external signer or credential store. Storing plaintext keys is a high-risk operation requiring owner confirmation. Required only when sign
    • low Secrets in code secret-high-entropy-token reference/agentbeat-submission.md:104
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "voucher": "agen…012",
      quoted
    • low Secrets in code secret-high-entropy-token reference/agentbeat-submission.md:167
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "voucher": "agen…012"
      quoted
    • low Secrets in code secret-high-entropy-token reference/erc8004-registration.md:17
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | Base | 8453 | `0x80…432` | `0x80…b63` | `https://mainnet.base.org` |
      table
    • low Secrets in code secret-high-entropy-token reference/erc8004-registration.md:18
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition; documentation table row)
      | Ethereum | 1 | `0x80…432` | `0x80…b63` | `https://eth.llamarpc.com` |
      detectortable
    • low Secrets in code secret-high-entropy-token reference/erc8004-registration.md:19
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | BNB Chain | 56 | `0x80…432` | `0x80…b63` | `https://bsc-dataseed.binance.org` |
      table
    • low Secrets in code secret-high-entropy-token reference/erc8004-registration.md:167
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const IDENTITY_REGISTRY = "0x80…432";
      quoted
    • low Secrets in code secret-high-entropy-token reference/erc8004-registration.md:182
      High-entropy token-like string (may be an id, hash or a credential)
      cast send 0x80…432 \
    • low Secrets in code secret-high-entropy-token reference/wallet-setup.md:157
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      USDC contract on Base: `0x83…913`
      quoted
    • low Secrets in code secret-high-entropy-token reference/wallet-setup.md:164
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      -d "{\"jsonrpc\":\"2.0\",\"method\":\"eth_call\",\"params\":[{\"to\":\"0x83…913\",\"data\":\"0x70…000${PADDED_ADDR}\"},\"latest\"],\"id\":1}
      quoted
    • low Secrets in code secret-high-entropy-token reference/x402-integration.md:154
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      asset: "0x83…913", // USDC on Base
      quoted
    • low Secrets in code secret-high-entropy-token reference/x402-integration.md:174
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - **USDC contract (Base)**: `0x83…913`
      quoted

    Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "required_tools"
    • note frontmatter-key unknown frontmatter key "env_vars"
    • note frontmatter-key unknown frontmatter key "credentials_path"

    Process rating: all ten parameters 63/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 55 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1684 tokens
    • 100Running it twice. Mutating operations check current state
    • low 11 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 427: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 55 items
    • +4Has examples (9 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.