AC oraclenet-mesh
Give an AI agent one route to live external data and MCP capabilities. Use when a task needs current blockchain, market, research, sanctions, weather, travel, or compliance data beyond the model's training cutoff. OracleNet discovers the relevant route, shows where pricing and verification metadata live, and starts with free discovery before any payment.
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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 · 4
✓ No critical or high findings
Medium and low: 4
-
low Secrets in code
secret-high-entropy-tokenreferences/x402-safety.md:45High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"payTo": "0x11…25D",
detector -
low Secrets in code
secret-high-entropy-tokenreferences/x402-safety.md:46High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)"asset": "0x83…913",
quoted -
low Secrets in code
secret-high-entropy-tokenreferences/x402-safety.md:84High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- `asset` is the USDC contract `0x83…913`
quoted -
low Risky intent
intent-wallet-secretsscripts/route.py:52Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target (detector / deny-list definition)("mnemonic seed phrase", re.compile(r"(?i)\b(?:seed|mnemonic|recovery)\s+phrase\b")),detector
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 357 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "repository"
Process rating: all ten parameters 56/100
- 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. 4 mutating operations with no state check
- 55Failures and branches. 1 branches
- 100Tools and files. No external tools needed
- 100Steps. 45 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3228 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 356: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 45 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.