SKILLEMALL.ai

BC expense-tracker

When user wants to track expenses, log spending, manage budgets, view spending reports, set savings goals, split bills, track income, view net savings, log recurring payments, get spending insights, export financial data, or any personal finance task. 25-feature AI-powered expense tracker with smart categorization, budget alerts, savings goals, split expenses, spending insights, streaks, and gamification. Works via natural language — just type "spent 50 on food" and done. Free alternative to Mint, YNAB, PocketGuard. All data stays local.

ClawHub Agent Skills author: Manish Pareek v1.0.0 2 files body ≈ 7 226 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Inputs and preconditions w 11
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 7226 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 52/100

  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 30 mutating operations with no state check
  • 40Consistency. Frontmatter name (expense-tracker) differs from the folder (smart-expense-tracker)
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Execution cost. Instruction body is 7226 tokens
  • 100Steps. 146 steps
  • 100Failures and branches. 8 branches, has a failure section
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 34 top-level sections: this looks like several domains in one skill
  • high The skill tells the model to perform an irreversible action with no human approval

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
  • -224 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 543: enough signal without eating the budget
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 146 items
  • +4Has examples (35 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill appears privacy-focused and local-only, but its activation scope is too broad for a tool that can read and modify personal finance records.
LLM: suspicious (medium) · VirusTotal: benign · 28 May 2026