BC teneo-protocol-cli
Teneo Protocol CLI — discover and query AI agents, manage rooms, and handle x402 USDC micropayments. Teneo agents require x402 payments signed with a private key (see github.com/AIMadeScripts/teneo-agent-sdk). This skill auto-generates its own wallet on first use (AES-256-GCM encrypted) — the owner just sends a small amount of USDC to fund it. Funds can be withdrawn back to the original funder at any time. No user keys are ever requested. Connects to the Teneo Protocol backend (wss://backend.developer.chatroom.teneo-protocol.ai). SDK: https://www.npmjs.com/package/@teneo-protocol/sdk
As a process C 57/100 · Has gaps — weak spots: inputs and preconditions, consistency, execution cost
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.
Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
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medium Risky intent
intent-wallet-secretsskill-card.md:23Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer targetMitigation: Do not provide a primary wallet private key; use the generated or otherwise dedicated wallet with limited funds and protect the local wallet files. <br>
-
low Secrets in code
secret-high-entropy-tokenskill.md:282High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)base: "0x83…913",
quoted -
low Secrets in code
secret-high-entropy-tokenskill.md:283High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)avax: "0xB9…a6E",
quoted -
low Secrets in code
secret-high-entropy-tokenskill.md:284High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)peaq: "0xbb…d10",
quoted -
low Secrets in code
secret-high-entropy-tokenskill.md:285High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)xlayer: "0x74…d22",
quoted
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Teneo Protocol CLI — discover and query AI agents, manage rooms, a… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
body-longSKILL.md body ≈ 11714 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 57/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 33 mutating operations with no state check
- 40Consistency. Frontmatter name (teneo-protocol-cli) differs from the folder (teneoprotocolcli)
- 40Execution cost. Instruction body is 11714 tokens: crowds the task out of the window
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 96 steps, 1 vague phrases
- 100Failures and branches. 19 branches, has a failure section
- 100Progress reporting. Reports progress
- 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
- low The response is described with custom markup (15 tags): a typed call is more reliable
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)
- -219 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 590: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 96 items
- +3Output format is stated explicitly
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.