SKILLEMALL.ai
GitHub ↗ RU Sign in

AC saas-metrics-dashboard

SaaS metrics calculator and dashboard builder for subscription businesses. Compute MRR, ARR, churn rate, NRR/GRR, LTV, CAC, CAC payback period, magic number, Rule of 40, quick ratio, and cohort retention. Accepts raw subscription data and outputs a structured metrics snapshot ready for investor reporting, board decks, or feeding into kpi-alert-system and startup-financial-model skills. Use when founders, CFOs, or analysts need a full SaaS health check, want to track metrics over time, or are preparing investor materials. NOT for: e-commerce or transactional businesses (no recurring revenue), real-time streaming data pipelines (use a dedicated BI tool), or QBO bookkeeping reconciliation (use qbo-automation). Not a replacement for a full data warehouse — designed for structured inputs and spot analysis.

ClawHub Agent Skills author: samledger67-dotcom v1.0.0 MIT-0 2 files body ≈ 2 318 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
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: 2. 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 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2318 tokens
    • low 10 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
    • +3Description length 812: 120–800 characters recommended
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 34 items
    • +3Output format is stated explicitly
    • +4Has examples (10 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This skill is a non-executable SaaS finance calculator template that is coherent with its stated purpose and does not request hidden access or privileges.
    LLM: benign (high) · VirusTotal: · 29 May 2026