SKILLEMALL.ai

AF revenuecat

RevenueCat metrics, customer data, and documentation search. Use when querying subscription analytics, MRR, churn, customers, or RevenueCat docs.

modbender/skill-library-mcp Agent Skills author: modbender MIT 18 files · 1 script body ≈ 897 tokens Open the sourcegithub.com analyzed 2 d ago

RevenueCat metrics, customer data, and documentation search.

As a process F 28/100 · Will not run — weak spots: steps, result and completion, when it triggers

IntegrationData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
F
28/100
Will not run
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
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: 18. 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 28/100

    • 0Steps. Prose only: no discrete steps
    • 0Result and completion. Does not say what the result is
    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 897 tokens

    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)
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 145: enough signal without eating the budget
    • +4Structure: 6 headings
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (14 of 16)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.