SKILLEMALL.ai

BC mandate

Use when enforcing spend limits on AI agent wallets, validating transactions before signing, configuring allowlists or approval workflows, detecting prompt injection in agent reasoning, scanning codebases for unprotected wallet calls, or auditing agent transaction history. Works with OpenClaw, Claude Code, GOAT, AgentKit, ElizaOS. Supports Bankr, Locus, Sponge, CDP wallets. Non-custodial: private keys never leave your machine.

ClawHub Agent Skills author: Roman v1.3.0 MIT-0 2 files body ≈ 5 174 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
76
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token SKILL.md:56
    High-entropy token-like string (may be an id, hash or a credential)
    Asset:    USDC (0x83…913)
  • low Secrets in code secret-high-entropy-token SKILL.md:153
    High-entropy token-like string (may be an id, hash or a credential)
    --to 0x03…F7e \
  • low Secrets in code secret-high-entropy-token SKILL.md:167
    High-entropy token-like string (may be an id, hash or a credential)
    --token 0x03…F7e \
  • low Secrets in code secret-high-entropy-token SKILL.md:471
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Ethereum | `0xA0…B48` | 6 |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:472
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Sepolia | `0x1c…238` | 6 |
    table

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5174 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, read, web) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5174 tokens
  • 100Steps. 34 steps
  • 100Failures and branches. 8 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 25 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 430: enough signal without eating the budget
  • +4Structure: 44 headings
  • +3Step-by-step instructions: 34 items
  • +3Output format is stated explicitly
  • +4Has examples (27 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
Mandate is a disclosed wallet-policy guard that handles sensitive transaction metadata, but its behavior is coherent with its stated purpose.
LLM: benign (high) · VirusTotal: · 29 May 2026