SKILLEMALL.ai

BC testing-patterns

Jest testing patterns, factory functions, mocking strategies, and TDD workflow. Use when writing unit tests, creating test factories, or following TDD red-green-refactor cycle.

The skillemall take

Jest testing patterns skill: factories, mocks, TDD cycle. Promises help with unit tests and red-green-refactor workflow. Files hold 1529 tokens of instructions, no critical errors. Quality 84, but process 64 means the description is solid while reproducibility lags. Never ran on models, no sandbox validation. Supports many platforms without actual verification on them.

Works as a cheat sheet for Jest structure and mocking if you're new to it. For experienced developers—more of a style reminder than revelation. Install if you write tests regularly and want consistent patterns, but don't expect miracles. It's a workflow guide, not a shortcut.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 1 529 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Jest testing patterns, factory functions, mocking strategies, and TDD workflow.

As a process C 64/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureSoftware developmenttype 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
C
64/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
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 64/100

    • 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. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 23 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1529 tokens
    • low 13 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 176: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 23 items
    • +4Has examples (12 code blocks)

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