BC guardrail-smart-accounts
Create and manage ERC-4337 smart accounts, policies, permissions, and enforcement for AI agents with on-chain spending guardrails.
Create and manage ERC-4337 smart accounts, policies, permissions, and enforcement for AI agents with on-chain spending guardrails.
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
GeneratorAI and agentsData and analyticstype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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-tokenSKILL.md:525High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| IdentityRegistry | `0xc1…104` |
table -
low Secrets in code
secret-high-entropy-tokenSKILL.md:526High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| PolicyRegistry | `0x92…8c4` |
table -
low Secrets in code
secret-high-entropy-tokenSKILL.md:527High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| PermissionEnforcer | `0xbF…61c` |
table -
low Secrets in code
secret-high-entropy-tokenSKILL.md:528High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| PriceOracle | `0xf3…5B3` |
table -
low Secrets in code
secret-high-entropy-tokenSKILL.md:529High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition; documentation table row)| GuardrailFeeManager | `0xD1…93A` |
detectortable
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 5015 tokens (recommended < 5000); move details to references/
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
- 0Failures and branches. Linear process with no failure handling
- 30Running it twice. 20 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 70Execution cost. Instruction body is 5015 tokens
- 100Tools and files. No external tools needed
- 100Steps. 72 steps
- 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 11 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 130: enough signal without eating the budget
- +4Structure: 34 headings
- +3Step-by-step instructions: 72 items
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.