SKILLEMALL.ai

BB stripe-automation

Automate Stripe tasks via Rube MCP (Composio): customers, charges, subscriptions, invoices, products, refunds. Always search tools first for current schemas.

The skillemall take

The skill promises Stripe task automation via Composio MCP: customers, charges, subscriptions, invoices, products, refunds. Single instruction file with 1909 tokens, no scripts. Scores: quality 84, process 64, safety 100. No critical errors, linter passes.

No sandbox or model runs on record. Covers many platforms but lacks execution examples, so it's unclear how it handles real Stripe API schemas. The instruction tells you to search for current tool schemas first — solid advice, but doesn't simplify the skill itself. Worth installing if you already work with Composio and MCP; otherwise expect a learning curve.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 2 080 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Automate Stripe tasks via Rube MCP (Composio): customers, charges, subscriptions, invoices, products, refunds.

As a process B 71/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice

GeneratorStripeAI and agentsCommerceFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
71/100
Nearly there
When it triggers w 12
20
Running it twice w 4
30
Result and completion w 14
40
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: agentic-awesome-skills

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: 1. 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 71/100

    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 50 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50Failures and branches. 0 branches, has a failure section
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 79 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2080 tokens
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 157: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 79 items
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.