AD job-offer-comparator
Use when comparing two or more job offers, deciding between a remote and on-site role, weighing a higher salary against a long commute, moving cities for a job, pricing the real value of benefits, or preparing a salary negotiation counter-offer. Computes true total compensation — base + expected bonus + capped retirement match + risk-discounted equity − health premiums − commute cost (km + parking) − cost-of-living adjustment — then effective hourly rate on REAL hours (contracted + overtime + commute), PTO valuation, and the exact break-even base salary the losing offer needs to match the winner. Outputs a negotiation-ready target number.
Use when comparing two or more job offers, deciding between a remote and on-site role, weighing a higher salary against a long commute, moving cities for a…
As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 47/100
- 0Result and completion. Does not say what the result is
- 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. 1 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 29 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2169 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
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 646: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (5 code blocks)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.