BB nex-expenses
Track and categorize all business expenses with automatic Belgian tax deduction rules and VAT recovery optimization. Use optical character recognition (OCR) with Tesseract to scan receipt images and automatically extract vendor names, transaction amounts, dates, and BTW rates from physical receipt photographs. Intelligently categorize expenses into Belgian tax deduction categories (beroepskosten 100%, representatie 50%, autokosten with fuel/other subcategories, kantoorkosten 100%, kledij/werkkledij, verzekeringen, opleiding, telecom, huurkantoor, etc.) with automatic deductible portion calculation per category following Belgian tax regulations. Generate quarterly summaries organized by tax category with total amounts, deductible amounts, effective deduction percentages, and BTW collected for convenient filing with your boekhouder (accountant). Track input VAT (BTW inkomsten) separately by rate (21%, 12%, 6%, 0%) for quarterly aangifte submissions and maintain complete payment method records (cash, bank transfer, credit card, debit card, cheque). Create professional CSV/JSON exports with Belgian-friendly column headers for import into accounting software. Ideal for freelancers, eenmanszaken, and kleine ondernemingen who need to manage expenses, optimize tax deductions, prepare quarterly accounting documents, and stay compliant with Belgian tax law. All expense data remains local.
As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting
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 skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Shorten the description to 1024 characters.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Dangerous commands
cmd-shell-rcsetup.sh:111Writes to a shell startup fileecho " Add this to your ~/.bashrc or ~/.zshrc"
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1401 chars, limit 1024
Process rating: all ten parameters 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 4 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
- 70When it triggers. States when to use, but not when not to
- 100Steps. 72 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3010 tokens
- low 11 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)
- +3Description length 1401: 120–800 characters recommended
- +2Single-language instructions
- +4Structure: 24 headings
- +3Step-by-step instructions: 72 items
- +3Output format is stated explicitly
- +4Has examples (15 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.