AC vestafolio-age-retraite
Simulate early retirement (FIRE) financed by invested capital for a French saver using Vestafolio's simulator API, after asking the simulator's questions (current situation, mortgage, target age, complementary income, lifestyle at retirement). Use when a user asks "à quel âge puis-je arrêter de travailler", "quand serai-je financièrement indépendant", at what age they can retire early, how much capital they need for FIRE, whether their savings will last, or how part-time income and expense cuts change their retirement age.
Simulate early retirement (FIRE) financed by invested capital for a French saver using Vestafolio's simulator API, after asking the simulator's questions…
As a process C 56/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
The same skill appears in 1 more place: ClawHub
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: 2. 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 56/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 65Failures and branches. 3 branches
- 85Steps. 36 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2339 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)
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 528: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 36 items
- +3Output format is stated explicitly
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.