SKILLEMALL.ai
RU Sign in

BC basecred-8004-registration

Interactive ERC-8004 agent registration via chat. Guides users through a prefill form, shows draft, confirms, then registers on-chain using agent0-sdk.

modbender/skill-library-mcp Agent Skills author: modbender MIT 11 files · 1 script body ≈ 3 320 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Interactive ERC-8004 agent registration via chat.

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

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
79/100
safety, quality, tests
Safety 60%
86
Quality 40%
69
Run on models
none yet
Process rating
C
59/100
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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:399
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    | `PRIVATE_KEY` / `AGENT_PRIVATE_KEY` / `MAIN_WALLET_PRIVATE_KEY` | Yes | Wallet private key |
  • low Secrets in code secret-high-entropy-token README.md:148
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Identity Registry: `0x80…432`
    quoted
  • low Secrets in code secret-high-entropy-token README.md:149
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Reputation Registry: `0x80…b63`
    quoted
  • low Secrets in code secret-high-entropy-token references/chains.md:4
    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 references/chains.md:5
    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 scripts/register.mjs:311
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    IDENTITY: '0x80…432',
    quoted
  • low Secrets in code secret-high-entropy-token scripts/register.mjs:312
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    REPUTATION: '0x80…b63',
    quoted
  • low Exfiltration read-dotenv SKILL.md:228
    Reads a .env file
    source /path/to/.env
  • low Secrets in code secret-high-entropy-token SKILL.md:305
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Identity Registry: `0x80…432`
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:306
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Reputation Registry: `0x80…b63`
    quoted

Files scanned: 11. 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")

Process rating: all ten parameters 59/100

  • 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
  • 30Running it twice. 5 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 12 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3320 tokens

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
  • -226 emoji in the instructions: noise for the model
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 151: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 12 items
  • +4Has examples (19 code blocks)
  • +3All 5 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.