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BC warren-deploy

Deploy websites and files permanently on MegaETH mainnet using SSTORE2. Agents use their own wallet and pay gas.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files · 1 script body ≈ 1 159 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Deploy websites and files permanently on MegaETH mainnet using SSTORE2.

As a process C 60/100 · Has gaps — weak spots: when it triggers, consistency, running it twice

ProcedureInfrastructuretype 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
83/100
safety, quality, tests
Safety 60%
82
Quality 40%
84
Run on models
none yet
Process rating
C
60/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
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.

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 · 10

    ✓ No critical or high findings

    Medium and low: 10
    • medium Risky intent intent-wallet-secrets SKILL.md:63
      Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
      | `PRIVATE_KEY` | **Yes** | — | Wallet private key for signing transactions |
    • medium Risky intent intent-wallet-secrets SKILL.md:100
      Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
      --private-key <key>   Wallet private key (or PRIVATE_KEY env)
    • low Secrets in code secret-high-entropy-token deploy.js:24
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const GENESIS_KEY_ADDRESS = process.env.GENESIS_KEY_ADDRESS || '0x0d…a88';
      quoted
    • low Secrets in code secret-high-entropy-token deploy.js:25
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const RABBIT_AGENT_ADDRESS = process.env.RABBIT_AGENT_ADDRESS || '0x3f…1f2';
      quoted
    • low Secrets in code secret-high-entropy-token deploy.js:26
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const MASTER_NFT_ADDRESS = process.env.MASTER_NFT_ADDRESS || '0xf2…eFC';
      quoted
    • low Risky intent intent-wallet-secrets deploy.js:304
      Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target (quoted — discussed, not commanded)
      --private-key <key>   Wallet private key (or set PRIVATE_KEY env)
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:27
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | Genesis Key NFT (0xRabbitNeo) | `0x0d…a88` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:28
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | 0xRa…ent Key NFT | `0x3f…1f2` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:29
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | MasterNFT Registry | `0xf2…eFC` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:54
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      Default `RABBIT_AGENT_ADDRESS`: `0x3f…1f2` (override via env).
      quoted

    Files scanned: 4. 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 60/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 12 mutating operations with no state check
    • 40Consistency. Frontmatter name (warren-deploy) differs from the folder (warren-deploy-mainnet)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 19 steps
    • 100Execution cost. Instruction body is 1159 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 112: 120–800 characters recommended
    • +1No license
    • +2Single-language instructions
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 19 items
    • +3Output format is stated explicitly
    • +4Has examples (10 code blocks)

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