A prompt coverage matrix is a fast way to audit whether a prompt actually addresses the situations it will face in production. Most prompt failures are not bad phrasing — they are silent gaps where an edge case (empty input, a hostile question, a missing field) was never mentioned, so the model improvises. This tool cross-references your prompt against a list of edge cases and flags which ones are explicitly handled, only implicitly covered, or completely unaddressed.
How it works
You paste two things: the prompt you want to audit, and a list of edge cases (one per line). The tool breaks each edge case into meaningful keywords, strips common stop-words, and checks how many of those keywords appear in the prompt. A high overlap is scored as handled, a partial overlap as partial (implicitly covered), and no overlap as a gap. It then reports an overall coverage percentage so you can track improvement as you tighten the prompt.
This is intentionally a local heuristic, not a model call. Keyword matching is transparent and instant, and it keeps confidential prompts on your machine. The trade-off is that it measures whether you mentioned a case, not whether your instruction for that case is correct.
Tips and examples
Seed your edge-case list with the universals — empty input, oversized input, adversarial or off-topic input, ambiguous wording, missing required data, non-English text, and conflicting instructions — then add cases specific to your task. For a support-reply prompt you might add “angry customer”, “refund request”, “out of scope”. After running the matrix, rewrite any gap rows into explicit instructions (“If the input is empty, ask the user for X”) and re-run until coverage is high and the partials become explicit. Treat the score as a checklist nudge, then validate the rewritten prompt against real inputs.