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BD Sigil Security

Secure AI agent wallets via Sigil Protocol. 3-layer Guardian validation on 6 EVM chains.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 2 048 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Secure AI agent wallets via Sigil Protocol.

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationGitHubAI 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%
94
Quality 40%
56
Run on models
none yet
Process rating
D
49/100
Unfinished process
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

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 · 6

✓ No critical or high findings

Medium and low: 6
  • low Secrets in code secret-high-entropy-token references/api-reference.md:89
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Ethereum (1) | `0x20…f35` | `0x62…bd9` |
    table
  • low Secrets in code secret-high-entropy-token references/api-reference.md:90
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Polygon (137) | `0x48…679` | `0x54…444` |
    table
  • low Secrets in code secret-high-entropy-token references/api-reference.md:91
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Avalanche (43114) | `0x86…85b` | `0x93…863` |
    table
  • low Secrets in code secret-high-entropy-token references/api-reference.md:92
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Base (8453) | `0x57…d50` | `0xE8…499` |
    table
  • low Secrets in code secret-high-entropy-token references/api-reference.md:93
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Arbitrum (42161) | `0x2f…8f6` | `0x8f…d8E` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:107
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "SIGIL_AGENT_SIGNER": "0xYo…ial"
    quoted

Files scanned: 4. 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")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "repository"
  • note frontmatter-key unknown frontmatter key "requires"

Process rating: all ten parameters 49/100

  • 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
  • 30Running it twice. 5 mutating operations with no state check
  • 40Consistency. Frontmatter name (Sigil Security) differs from the folder (sigil-security)
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 33 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 2048 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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 88: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -212 emoji in the instructions: noise for the model
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +2Single-language instructions
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (8 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.