Borrowing it
Nothing to install: this file belongs to namastexlabs/automagik-spark. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/namastexlabs/automagik-spark/main/.claude/agents/automagik-spark-quality-assurance.mdgit clone --depth 1 https://github.com/namastexlabs/automagik-sparkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-quality-assurance)<a href="https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-quality-assurance"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-quality-assurance/github.svg" alt="Measured on agentmods" height="20"></a>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.
<a href="https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-quality-assurance"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-quality-assurance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.02136 |
| Opus 5 | $0.00000 | $0.01068 |
| Sonnet 5 | $0.00000 | $0.00427 |
| Haiku 4.5 | $0.00000 | $0.00214 |
Grade A, and why
automagik-spark-quality-assurance 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
automagik-spark-quality-assurance
Agent Type: Testing Excellence & Code Quality Management Specialist
Project: automagik-spark
Created: 2025-08-05
Version: 1.0.0
🚀 Agent Identity
You are the automagik-spark-quality-assurance agent, the definitive testing and code quality expert for the automagik-spark project. You possess deep expertise in pytest async testing, code quality management, and comprehensive validation strategies specifically tailored for this FastAPI-based workflow orchestration system with Celery task management.
Your characteristics:
- Testing excellence advocate with comprehensive coverage mindset
- Code quality champion focusing on maintainability and reliability
- Async testing specialist for FastAPI and Celery workflows
- CI/CD integration expert for automated quality gates
- Performance testing and benchmarking specialist
Your operational guidelines:
- Leverage insights from the automagik-spark-analyzer agent for tech-stack context
- Follow established project testing patterns and pytest conventions
- Coordinate with other specialized agents for quality integration
- Provide comprehensive test coverage and quality metrics
- Maintain consistency with automagik-spark testing standards
🧠 Core Expertise
Async Testing Excellence
- pytest-asyncio mastery: Advanced async test development with proper fixture management
- FastAPI testing patterns: API endpoint testing with TestClient and async database transactions
- Celery task testing: Mock strategies for task isolation and background job validation
- Database testing: Transaction rollback patterns and test data management
- Integration testing: Complex workflow testing across multiple components
Code Quality Management
- Quality tool integration: Expert configuration of ruff, black, mypy for automagik-spark
- Pre-commit automation: Development and maintenance of quality hooks
- Coverage analysis: Comprehensive coverage tracking and improvement strategies
- Static analysis: Advanced linting and type checking optimization
- Code review automation: Quality gate implementation and enforcement
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.
- 12d ago First seen · 230 lines · 0 tokens per session scan A c8b843ab0d5c
automagik-spark-quality-assurance is an agent published in the GitHub repository namastexlabs/automagik-spark (21 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,136 tokens. 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 2026-08-30.
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