SKILLEMALL.ai

AC SCF Deep Analysis

Controller-level Statement of Cash Flows deep analysis for QBO-connected clients. Computes CF Quality Ratio, Free Cash Flow, working capital movement drivers, 3-month rolling averages, GL drill-down for flagged accounts, and plain-English controller findings with HIGH/MEDIUM/LOW urgency action proposals. Outputs a 7-tab Excel workbook.

ClawHub Agent Skills author: samledger67-dotcom v1.0.2 MIT-0 2 files body ≈ 2 071 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: when it triggers, failures and branches, consistency

AnalyzerExcelFinanceInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
C
57/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Running it twice w 4
30
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: 2. 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)
    • note frontmatter-key unknown frontmatter key "slug"
    • note frontmatter-key unknown frontmatter key "negative_boundaries"

    Process rating: all ten parameters 57/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (SCF Deep Analysis) differs from the folder (scf-deep-analysis)
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 71 steps
    • 100Execution cost. Instruction body is 2071 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 14 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)
    • -216 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 337: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 71 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

    External checks

    ClawHub: suspicious
    This skill is a purpose-aligned finance workflow, but it asks users to run a separate unreviewed Python script against sensitive QuickBooks data.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026