BC expense-tracker
Just say what you spent — your AI logs it, categorizes it, and tracks it against your budget. No apps, no forms, no friction. Supports natural language like 'spent $45 at Costco' or 'split a $90 dinner with Jake'. 16 auto-categories, monthly budget alerts, weekly and monthly reports. Runs entirely local — your spending data stays on your machine.
Just say what you spent — your AI logs it, categorizes it, and tracks it against your budget.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 348 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill
Process rating: all ten parameters 51/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (expense-tracker) differs from the folder (nicholasrae-expense-tracker)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 85Steps. 73 steps, 1 vague phrases
- 100Failures and branches. 2 branches, has a failure section
- 100Execution cost. Instruction body is 3958 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 tags): a typed call is more reliable
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 348: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 73 items
- +4Has examples (9 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.