BC outsmart-lp-farming
Manage LP positions on Solana DEXes to earn swap fees. Use when: user asks about LP farming, providing liquidity, earning yield, compounding fees, DLMM, DAMM v2, rebalancing, creating pools, passive income on Solana. NOT for: lending/borrowing protocols, staking SOL, CEX market making.
As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Risky intent
intent-wallet-secretsskill-card.md:19Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer targetRisk: The skill uses a raw Solana wallet private key and an external CLI that can initiate irreversible financial transactions. <br>
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medium Risky intent
intent-wallet-secretsskill-card.md:20Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer targetMitigation: Use a dedicated low-balance wallet, avoid exposing a main wallet private key, and manually review or simulate transactions before execution. <br>
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 60/100
- 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
- 30Running it twice. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 100Tools and files. No external tools needed
- 100Steps. 13 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 906 tokens
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
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 286: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 13 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.