testing-scaffold

testing-scaffold is a skill for Claude Code, Codex from mexmarv/ai-genie-factory. It costs 80 tokens per session (1,092 once invoked), scanned A, original, MIT.

A test-writing guide for Databricks Apps, which are applications that run on the Databricks data platform. It sets a standard structure for pytest unit tests, including mocked data-service calls and small pandas tables.

In plain words
What is it for?
Use it when creating, reviewing, or fixing tests, test stubs, mocks, or failing tests in a Databricks App.
Why use it?
It helps catch errors without connecting tests to live Databricks data, a warehouse, or Spark. It also ensures every app has tests from the start.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when creating, reviewing, or fixing tests, test stubs, mocks, or failing tests in a Databricks App.

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Install with agentmods
npx agentmods add skills/mexmarv/ai-genie-factory/testing-scaffold
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add mexmarv/ai-genie-factory --skill testing-scaffold
Clone the repo
git clone --depth 1 https://github.com/mexmarv/ai-genie-factory

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,092 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00080 $0.01092
Opus 5 $0.00040 $0.00546
Sonnet 5 $0.00016 $0.00218
Haiku 4.5 $0.00008 $0.00109

Measured 11d ago against content hash 779607bb74b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

testing-scaffold scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/testing-scaffold/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Testing Scaffold

Every generated app must include tests/test_data.py and tests/test_logic.py. Tests must be present even if minimal — this enforces testability from day one.

Rules

  • Data layer tests mock data.WorkspaceClient — never hit Unity Catalog or the warehouse
  • Logic layer tests use small hardcoded pandas DataFrames
  • Always use pytest — no unittest directly
  • Test function names: test_<function>_<condition>
  • No Spark, no live Databricks SDK calls in any test

tests/test_data.py

"""Tests for data.py — all WorkspaceClient calls are mocked."""
import pytest
import pandas as pd
from unittest.mock import patch, MagicMock
from data import DataAccessError, load_orders


def _make_result(rows, cols, state="SUCCEEDED", error_message=None):
    """Helper: build a mock Statement Execution result."""
    result = MagicMock()
    result.status.state.value = state
    result.status.error.message = error_message
    result.manifest.schema.columns = [MagicMock(name=c) for c in cols]
    for column, name in zip(result.manifest.schema.columns, cols):
        column.name = name
    result.result.data_array = rows
    return result


@patch("data.WorkspaceClient")
def test_load_orders_returns_dataframe(mock_client_cls):
    mock_client = mock_client_cls.return_value
    mock_client.statement_execution.execute_statement.return_value = _make_result(
        rows=[["2024-01-01", "North", "100.0", "1", "1"]],
        cols=["order_date", "region", "amount", "order_id", "customer_id"],
    )

    config = {"table_name": "prod.gold.orders", "warehouse_id": "wh-1", "row_limit": 1000}
    df = load_orders(config, "2024-01-01", "2024-01-31")
    assert isinstance(df, pd.DataFrame)
    assert list(df.columns) == ["order_date", "region", "amount", "order_id", "customer_id"]
    assert len(df) == 1


@patch("data.WorkspaceClient")
def test_load_orders_raises_data_access_error_on_failure(mock_client_cls):
    mock_client = mock_client_cls.return_value
    mock_client.statement_execution.execute_statement.side_effect = Exception("Warehouse timeout")

    config = {"table_name": "prod.gold.orders", "warehouse_id": "wh-1", "row_limit": 1000}
    with pytest.raises(DataAccessError, match="unavailable"):
        load_orders(config, "2024-01-01", "2024-01-31")


@patch("data.WorkspaceClient")
def test_load_orders_raises_on_non_gold_schema(mock_client_cls):
    config = {"table_name": "prod.silver.orders", "warehouse_id": "wh-1", "row_limit": 1000}
    with pytest.raises(DataAccessError, match="Gold"):
        load_orders(config, "2024-01-01", "2024-01-31")
    mock_client_cls.return_value.statement_execution.execute_statement.assert_not_called()

Read the full file on GitHub · 135 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 135 lines · 80 tokens per session scan A 779607bb74b9

Subscribe to this mod's changes

testing-scaffold is a skill published in the GitHub repository mexmarv/ai-genie-factory (5 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 1,092 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.