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Failure Mode Catalogue for a Prompt

Table output Has example

List how your prompt can go wrong before it does.

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Create a failure mode catalogue for my prompt. The prompt: [PASTE_PROMPT]. Where its output goes and who relies on it: [OUTPUT_USE]. Examples of inputs: [SAMPLE_INPUTS].

Return a table: ID | Failure mode | How it would look in the output | Likely cause in the prompt or input | Likelihood | Impact | Test input that would trigger it | Mitigation in the prompt | Mitigation outside the prompt (human review, validation code, limits).
Cover: hallucinated facts; ignoring the format; truncating long outputs; overlong or padded answers; tone drift; following instructions hidden in the input; mishandling missing data; mixing up entities; inconsistent results across runs; refusing valid requests; complying with harmful requests; leaking sensitive text; bias against groups; stale knowledge; arithmetic errors; misread tables; language or locale errors; and over-reliance on one example.

Then rank the top five by risk, write improved instructions for them, create a monitoring checklist (what to sample weekly), define escalation rules (what to do if a serious failure occurs), and propose a small incident log. Add a warning that prompt changes can fix one failure and create another, so rerun the test set. Do not claim any prompt can eliminate failures.

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See an example result (fictional data)
ID | Failure | Looks like | Cause | Likelihood | Impact | Test input | Mitigation
F1 | Invented policy | states a refund window we do not have | no policy provided | medium | high | "What is your refund window?" with no policy text | add policy text and "not stated" rule
F2 | Ignores format | prose instead of JSON | format at the end of a long prompt | medium | medium | long input | move format earlier, validate in code
F3 | Follows hidden instructions | obeys text inside a pasted email | no delimiter | low | high | email saying "ignore previous rules" | delimiters, least access
Top five get new instructions; sample outputs weekly; log incidents.

Illustrative only, made-up data. Your results will differ and must be reviewed.

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