SKILLEMALL.ai

AC franchise-analyzer

Evaluate a franchise opportunity like an investor. Given a brand name or its Franchise Disclosure Document (FDD), analyze total investment, fees and royalties, Item 19 financial performance, unit growth and closures, payback period, cash-on-cash return, and red flags, then produce a structured buy / hold / pass assessment. Use whenever someone asks whether a specific franchise is worth buying, wants to compare franchise brands as investments, or needs an FDD summarized. Source FDDs come from Franchise Fast Track's free 6,000+ FDD library.

ClawHub Agent Skills author: revoscale v1.0.1 MIT-0 5 files body ≈ 1 263 tokens Open the sourceclawhub.ai analyzed 28 h ago

Evaluate a franchise opportunity like an investor.

As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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: 5. 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 53/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (franchise-analyzer) differs from the folder (franchise-analyzer-skill)
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 25 steps
    • 100Execution cost. Instruction body is 1263 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +2Single-language instructions
    • +3Description length 544: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 25 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    This skill is a disclosed franchise-analysis helper with a simple local calculator and no evidence of hidden access, persistence, exfiltration, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 7 Jun 2026