A free tool scores how likely a prompt is to fail

A prompt can carry cognitive load: the amount of reasoning, tool use, rule tracking, and output formatting it asks a model to handle in one call. When that load is high, the model may not refuse, but it can skip steps, mix up instructions, or return answers that look reasonable but are wrong.

This tool scores that failure risk with fixed rules, runs locally, and does not make extra LLM calls. The scoring approach has 9 dimensions; the shared details include task count, reasoning depth, tool complexity, constraint density, and output complexity.

Task count looks at how many separate action instructions appear, with risk rising when there are more than about 4. Reasoning depth looks at nested if-then branches, tool complexity looks at how many tools or APIs are mentioned, constraint density looks at how packed the prompt is with rules, and output complexity looks at how many result formats are required.