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BD chaoschain

Verify AI agent identity and reputation via ERC-8004 on-chain registries

modbender/skill-library-mcp Agent Skills author: modbender MIT 9 files · 1 script body ≈ 1 655 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Verify AI agent identity and reputation via ERC-8004 on-chain registries

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI 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%
88
Quality 40%
66
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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.
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
  • low Secrets in code secret-high-entropy-token README.md:171
    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 README.md:172
    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 README.md:187
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    `IdentityRegistry` `0x80…D9e`
    quoted
  • low Secrets in code secret-high-entropy-token README.md:188
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    `ReputationRegistry` `0x80…713`
    quoted
  • low Secrets in code secret-high-entropy-token scripts/chaoschain_skill.py:27
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    MAINNET_IDENTITY_REGISTRY = "0x80…432"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/chaoschain_skill.py:28
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    MAINNET_REPUTATION_REGISTRY = "0x80…b63"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/chaoschain_skill.py:29
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    TESTNET_IDENTITY_REGISTRY = "0x80…D9e"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/chaoschain_skill.py:30
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    TESTNET_REPUTATION_REGISTRY = "0x80…713"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:237
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Mainnet (all supported mainnet chains) | Identity | `0x80…432` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:238
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Mainnet (all supported mainnet chains) | Reputation | `0x80…b63` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:239
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Testnet (all supported testnet chains) | Identity | `0x80…D9e` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:240
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Testnet (all supported testnet chains) | Reputation | `0x80…713` |
    table

Files scanned: 9. 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 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 47 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1655 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 72: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -35 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.