AC finops
Expert FinOps (Cloud Financial Operations) guidance for cloud cost optimization, financial management, and business value maximization. Use for cloud cost management, AWS/Azure/GCP billing, cost allocation, tagging strategies, Reserved Instances, Savings Plans, Committed Use Discounts, rightsizing, forecasting, budgeting, showback/chargeback, unit economics, FinOps maturity assessment, governance policies, anomaly detection, rate optimization, workload optimization, cloud sustainability, or any cloud financial operations questions. Follows FinOps framework standards.
Expert FinOps (Cloud Financial Operations) guidance for cloud cost optimization, financial management, and business value maximization.
As a process C 55/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice
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 · 0
✓ No critical or high findings
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5020 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 55/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 31 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 5020 tokens
- 85Steps. 172 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 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)
- +2Single-language instructions
- +3Description length 573: enough signal without eating the budget
- +4Structure: 55 headings
- +3Step-by-step instructions: 172 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.