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BD Agent Security Auditor

Scans ERC-8004 agents for security vulnerabilities and generates comprehensive security reports.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 739 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Scans ERC-8004 agents for security vulnerabilities and generates comprehensive security reports.

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsData and analyticstype 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%
93
Quality 40%
71
Run on models
none yet
Process rating
D
39/100
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 · 7

✓ No critical or high findings

Medium and low: 7
  • low Secrets in code secret-high-entropy-token references/ERC-8004.md:9
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    **Address**: `0x80…432`
    quoted
  • low Secrets in code secret-high-entropy-token scripts/audit.js:13
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const IDENTITY_REGISTRY_ADDRESS = '0x80…432';
    quoted
  • low Secrets in code secret-high-entropy-token scripts/audit.js:180
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    '0x8b…123', // Common pattern, may need to be discovered
    quoted
  • low Secrets in code secret-high-entropy-token scripts/audit.js:565
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    console.log('  node audit.js 0x74…E21');
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:41
    High-entropy token-like string (may be an id, hash or a credential)
    node scripts/audit.js 0x74…E21
  • low Secrets in code secret-high-entropy-token SKILL.md:44
    High-entropy token-like string (may be an id, hash or a credential)
    node scripts/audit.js 0x74…E21 --rpc https://mainnet.infura.io/v3/YOUR_KEY
  • low Secrets in code secret-high-entropy-token SKILL.md:47
    High-entropy token-like string (may be an id, hash or a credential)
    node scripts/audit.js 0x74…E21 --output report.json

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

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 39/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (Agent Security Auditor) differs from the folder (agent-security-auditor)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 29 steps
  • 100Execution cost. Instruction body is 739 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)
  • +3Description length 96: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.