AC sentinel-transaction-safety
Pre-execution transaction safety check for autonomous AI agents — one capability of the SENTINEL trust oracle (sentinel-agent.dev). Before signing an on-chain transaction on Base, an agent calls SENTINEL and receives a SAFE / UNSAFE / UNKNOWN verdict, a SENTINEL Score (0-100, grade AAA-D), and an ed25519-signed receipt. Checks contract security (GoPlus token security) and execution simulation (Alchemy eth_call). Pay-per-call via x402 on Base — pricing is tiered by transaction value (from $0.005 USDC for small txs, scaling up for higher-value ones). No accounts, no API keys, no SDK required. No free trial. SENTINEL also exposes a separate counterparty-trust capability (behavioral 0-100 scoring); see "SENTINEL is one oracle with two capabilities" below.
Pre-execution transaction safety check for autonomous AI agents — one capability of the SENTINEL trust oracle (sentinel-agent.dev). Before signing an on-chain…
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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:22High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)oracle_onchain: "0x68…813 (Base)"
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:27High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)usdc_asset: "0x83…913 (USDC on Base)"
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:28High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)pay_to: "0xCf…7E7"
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:41High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)> ℹ️ **Name notice:** This is `sentinel-agent.dev` (on-chain oracle `0x68…813`), distinct from unrelated projects sharing the SENTINEL name.
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:110High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- **On-chain oracle (Base):** `0x68…813`
quoted
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 51/100
- 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. 7 mutating operations with no state check
- 40Consistency. Frontmatter name (sentinel-transaction-safety) differs from the folder (sentinel-public)
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 40 steps
- 100Execution cost. Instruction body is 2860 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 761: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 40 items
- +4Has examples (4 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.