SKILLEMALL.ai

AC finance-analyzer

This skill should be used when a user needs to analyze financial statements (Income Statement, Balance Sheet, Cash Flow Statement) from Excel or CSV files. It extracts financial data and calculates key metrics such as ROE, ROA, gross margin, and net margin. Trigger scenarios include requests like "analyze this financial report", "calculate ROE/ROA", "what's the gross margin", or any task involving reading and interpreting financial spreadsheets.

ClawHub Agent Skills author: zhengmengkaiZMK v1.0.1 MIT-0 4 files body ≈ 921 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 59/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, progress reporting

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
100/100
safety, quality, tests
Safety 60%
100
Quality 40%
99
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    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: 4. 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 59/100

    • 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
    • 60Tools and files. Uses tools (read, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Failures and branches. 4 branches
    • 85Steps. 23 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 921 tokens
    • 100Running it twice. No mutating operations

    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 3 example trigger phrases
    • +3Description length 449: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 23 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 99.

    External checks

    ClawHub: clean
    This skill locally analyzes user-provided financial spreadsheets and does not show hidden data sharing, credential use, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026