SKILLEMALL.ai

BB Money

Decides where money goes next: which debt to clear first, how big the emergency fund must be, what to save, and whether a purchase is affordable. Use when the question is "should I pay this off or invest it", "how much do I need saved", "can I afford this", "rent or buy", "am I on track to stop working", or "where does my money even go"; when a raise, bonus, inheritance, equity vest or business sale lands and nobody has decided what to do with it; when a card is at 20% and only minimums are going out; when a job ends, a diagnosis arrives, a marriage ends, or income suddenly swings; when a credit score drops or a loan is refused; or when judging a pitch, an adviser's fee, or a "guaranteed" return. Covers savings rate, order of operations, real-versus-nominal maths, and fee drag. Not for picking funds or brokers (`invest`), building a tracker or importing statements (`personal-finance-tracker`), a recurring-payment list (`subscriptions`), or company finance (`cfo`).

ClawHub Agent Skills author: Iván v1.0.2 MIT-0 21 files body ≈ 6 302 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 67/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • 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: 21. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning body-long SKILL.md body ≈ 6302 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 67/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 10 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
  • 70Failures and branches. 5 branches
  • 70Execution cost. Instruction body is 6302 tokens
  • 100Steps. 44 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • 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

  • +3Description length 978: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 7 example trigger phrases
  • +4Description says when NOT to use the skill
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 44 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This is a coherent personal-finance skill, but it automatically reads and modifies sensitive local financial records without per-write confirmation.
LLM: suspicious (high) · 27 Jul 2026