Promptfoo
CLI and CI-integrated LLM test harness that runs YAML-defined test suites across models and prompts, with built-in automated red-teaming and prompt injection testing.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
LLM API keys stored in environment variables or config files — ensure promptfoo config files are gitignored if they contain keys. Red-team results may contain sensitive adversarial outputs; secure storage recommended.
⚡ Reliability
Best When
You want to integrate LLM quality and safety regression tests into a CI/CD pipeline with YAML-defined test cases and model comparison without writing custom test infrastructure.
Avoid When
You need real-time output validation or conversation flow control — promptfoo evaluates offline test suites, not live requests.
Use Cases
- • Regression testing LLM prompts in CI/CD pipelines to catch quality degradations before deploying prompt changes to production
- • Side-by-side comparison of multiple models (GPT-4o vs Claude vs Gemini) on the same test suite to drive model selection decisions
- • Automated red-teaming that generates adversarial inputs to probe for jailbreaks, PII leakage, and harmful content generation
- • Evaluating RAG pipeline quality by defining test cases with expected retrieved context and checking answer faithfulness
- • A/B testing prompt variants with statistical assertions to determine which version performs better on a labeled dataset
Not For
- • Runtime production guardrails — promptfoo is a test harness, not a middleware layer that intercepts live traffic
- • Building agent workflows or orchestrating multi-step LLM pipelines — use LangGraph or Agno for that
- • Teams that need a GUI-first evaluation platform without CLI or YAML configuration
Interface
Authentication
LLM provider API keys set via environment variables or promptfoo config. Promptfoo Cloud sharing features require a free account.
Pricing
MIT open source. Primary costs are LLM API calls consumed during test runs and red-team generation.
Agent Metadata
Known Gotchas
- ⚠ Red-team generation makes many LLM calls to create adversarial inputs — large test suites can exhaust API rate limits without --concurrency tuning
- ⚠ promptfoo is a test harness, not a runtime library — agents trying to use it for live validation are misusing the tool
- ⚠ YAML test files are the primary interface; teams accustomed to code-first testing frameworks find the YAML-only approach limiting for complex assertion logic
- ⚠ Model comparison results are snapshot-in-time — LLM provider model updates can change results without any code or config change
- ⚠ The built-in LLM grader for subjective assertions (e.g., 'is this response helpful?') is itself an LLM call that adds cost and introduces evaluation variance
Alternatives
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Scores are editorial opinions as of 2026-03-07.