AC defi-yield-monitor
Monitor DeFi lending & savings positions across Aave v3, SparkLend, Spark Savings, and Kamino. Track balances, APY, health factors, and compute 7d/30d realized yield. No API keys required. Use when user asks about DeFi positions, lending yields, stablecoin earnings, portfolio health, or wants automated DeFi reporting. Triggers: "check DeFi", "lending yield", "DeFi收益", "持仓", "APY", "health factor", "stablecoin yield", "Aave", "Spark savings", "Kamino", "DeFi report".
As a process C 55/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice
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 · 0
✓ No critical or high findings
Files scanned: 4. 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: Monitor DeFi lending & savings positions across Aave v3, SparkLend… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 55/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 3 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 6 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 670 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
- +4Description does not say when NOT to use the skill (false activations)
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 470: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 6 items
- +3Output format is stated explicitly
- +4Has examples (6 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.