Spikee — Prompt Injection Eval Kit (CLI)

Main

• Follow the two-stage loop in README: generate datasets from seed folders, then test a target with consistent judges/providers.

• Keep installs lean: README says the default install targets OpenAI-compatible endpoints; use extras only for providers you need.

• Treat results as evidence: keep JSONL datasets + configs and re-run generate + test in CI or on release candidates.

Source-backed notes

• README says Spikee migrated away from LangChain to any-llm to reduce dependency bloat, with optional extras like spikee[all].
• README quickstart uses pip install spikee, then spikee init for a workspace and spikee list for modules.
• README describes dataset generation (spikee generate) and testing (spikee test) as the core workflow stages.

FAQ

• Is Spikee only for standalone models?: No — README includes LLM applications/agents and guardrails as targets.
• Do I have to install heavyweight SDKs?: No — README says the default install stays minimal and provider SDKs are optional extras.
• How do I keep evals repeatable?: Version your seed folders/datasets and re-run with pinned providers/judges.