Fai Pytest Coverage

name: fai-pytest-coverage description: "Generate Python pytest test suites with fixtures, parametrization, mocking (pytest-mock), and coverage reports." waf: ["Reliability", "Operational Excellence"] plays: ["32-test-generation", "24-code-assistant"]

Fai Pytest Coverage

Generates pytest test suites with fixtures, parametrize, mocks, and coverage configuration.

Overview

This skill provides a structured, repeatable procedure for generates pytest test suites with fixtures, parametrize, mocks, and coverage configuration.. It can be used standalone as a LEGO block or auto-wired inside solution plays via the FAI Protocol.

Category: Testing Complexity: Medium Estimated Time: 10-30 minutes

Parameters

Steps

Step 1: Validate Prerequisites

Verify all required tools, credentials, and dependencies are available.

# Check required tools
command -v node >/dev/null 2>&1 || { echo 'Node.js required'; exit 1; }
command -v az >/dev/null 2>&1 || { echo 'Azure CLI required'; exit 1; }

Step 2: Load Configuration

Read settings from the FAI manifest and TuneKit config files.

# Load from fai-manifest.json if inside a play
CONFIG_DIR="${config_path:-config}"
if [ -f "fai-manifest.json" ]; then
  echo "FAI Protocol detected — auto-wiring context"
fi

Step 3: Execute Core Logic

Perform the primary operation: generates pytest test suites with fixtures, parametrize, mocks, and coverage configuration..

Step 4: Validate Results

Verify the output meets quality thresholds and WAF compliance.

# Validate output
if [ "$?" -eq 0 ]; then
  echo "✅ Skill completed successfully"
else
  echo "❌ Skill failed — check logs"
  exit 1
fi

Output

WAF Alignment

Compatible Solution Plays

• Play 32

Error Handling

Usage

Standalone

# Run this skill directly
npx frootai skill run fai-pytest-coverage

Inside a Solution Play

When referenced in fai-manifest.json, this skill auto-wires with the play's context:

{
  "primitives": {
    "skills": ["skills/fai-pytest-coverage/"]
  }
}

Via Agent Invocation

Agents can invoke this skill using the /skill command in Copilot Chat.

RAG Pipeline Reference

Chunking Strategy

from azure.ai.formrecognizer import DocumentAnalysisClient

# Semantic chunking preserves paragraph boundaries
chunks = semantic_chunk(
    text=document,
    max_tokens=512,
    overlap_tokens=50,
    respect_boundaries=True  # Don't split mid-sentence
)

Search Configuration

{
  "search_type": "hybrid",
  "semantic_weight": 0.6,
  "keyword_weight": 0.4,
  "top_k": 5,
  "min_score": 0.78,
  "reranker": "semantic",
  "filter": "category eq 'technical'"
}

Notes

• This skill follows the FAI SKILL.md specification
• All outputs are deterministic when dry_run=true
• Integrates with FAI Engine for automated pipeline execution
• Part of the Testing category in the FAI primitives catalog

Source: frootai/frootai — distributed by TomeVault.