QuillBot Prompts

Take this draft business proposal text: [PASTE_DRAFT]. Run it through QuillBot's Paraphraser in Formal mode to elevate the tone for [AUDIENCE, e.g. enterprise procurement]. Requirements: keep every number, date, and commitment exactly as written ([PROTECTED_FACTS]); convert casual phrasing to professional business language; keep sentences under 25 words; preserve the section structure ([SECTIONS]). After paraphrasing, run the Grammar Checker and list any remaining issues. Output: the Formal-mode paraphrase, a short list of the 5 most improved sentences (before/after), and any factual ambiguities you noticed that a human must verify. Constraints: no meaning changes; flag any paraphrase that alters a commitment.

Polish this text written by a non-native English speaker: [PASTE_TEXT]. Use QuillBot's Paraphraser in Fluency mode so it reads naturally to [TARGET_READERS]. Focus on: article usage, preposition choice, word order, and idiomatic phrasing, while keeping the author's voice ([VOICE_NOTES]) and all technical terms ([TECHNICAL_TERMS] must stay unchanged). Then run the Grammar Checker. Output: the Fluency paraphrase plus a table of the top 8 corrections (original phrase, corrected phrase, rule name) so the author learns from them. Constraints: do not simplify ideas; do not change the argument structure; mark any sentence whose meaning is unclear rather than guessing.

Generate headline variations for [CAMPAIGN] using QuillBot's Paraphraser in Creative mode. Seed headlines: [SEED_HEADLINES]. Audience: [AUDIENCE]; promise: [CORE_PROMISE]; tone: [TONE]. Produce 12 variations, each under [CHAR_LIMIT] chars, grouped by angle ([ANGLE_1], [ANGLE_2], [ANGLE_3]). Every variation must stay truthful to [APPROVED_CLAIMS]. After generating, note which 3 you would A/B test first and why. Constraints: no clickbait that the landing page ([LANDING_URL_NOTES]) cannot support; keep brand voice [BRAND_VOICE_NOTES]; avoid the banned words [BANNED_WORDS].

Tighten this [WORD_COUNT]-word report to under [TARGET_WORDS] words using QuillBot's Paraphraser in Shorten mode: [PASTE_REPORT]. Preserve: the executive summary's conclusions ([KEY_CONCLUSIONS]), all data points ([DATA_POINTS]), and the recommendations ([RECOMMENDATIONS]). Cut: redundancies, throat-clearing, and repeated examples ([SECTIONS_TO_TRIM]). Output the shortened version with a 5-line changelog of what was cut and why. Constraints: no new information; every retained number must match the original; if a cut would remove nuance a decision-maker needs, flag it instead of cutting.

Expand this thin draft into a full [TARGET_WORDS]-word article using QuillBot's Paraphraser in Expand mode: [PASTE_DRAFT]. Topic: [TOPIC] for [AUDIENCE] at [READING_LEVEL]. Add: concrete examples ([EXAMPLE_DIRECTIONS]), transitions between sections ([SECTIONS]), and a brief explanation wherever the draft assumes knowledge ([ASSUMED_KNOWLEDGE_POINTS]). Mark every added example or claim with [ADDED] so a human can fact-check them. Constraints: do not invent statistics; keep the author's original thesis ([THESIS]) intact; added content must be clearly marked; run the Grammar Checker at the end.

Summarize this research paper for a [ROLE, e.g. product manager] with [TIME_AVAILABLE] to read: [PASTE_PAPER_OR_ABSTRACT]. Use QuillBot's Summarizer to produce: a 3-sentence TL;DR, 5 key findings as bullets, the methodology in 2 sentences, limitations in 2 sentences, and one paragraph on what it means for [DECISION_CONTEXT]. Keep all numbers exact ([KEY_NUMBERS] must appear verbatim). Constraints: do not overstate conclusions beyond what the paper claims; distinguish the paper's claims from your interpretation; note the sample size and date ([STUDY_META]).

Build a reference list for [PAPER_TITLE] ([COURSE_OR_PUBLICATION]) using QuillBot's Citation Generator in [CITATION_STYLE, e.g. APA 7]. Sources: [SOURCE_1_DETAILS], [SOURCE_2_DETAILS], [SOURCE_3_DETAILS], [SOURCE_4_DETAILS] (add more as needed). For each source provide: the generated citation, the source type, and which claim in my paper it supports ([CLAIM_MAPPING]). Then verify each citation has all required fields for [CITATION_STYLE] and flag any missing metadata (DOI, page numbers, retrieval dates) I must supply. Constraints: never fabricate a DOI or page number; mark incomplete citations clearly; cross-check author names against [SOURCE_OF_TRUTH].

Final proofread of this [DOCUMENT_TYPE] before [DEADLINE_OR_SUBMISSION]: [PASTE_TEXT]. Run QuillBot's Grammar Checker and report: all grammar, punctuation, and spelling issues grouped by type, with the suggested fix and a one-line rule explanation for each of the top 10. Also check consistency of: terminology ([KEY_TERMS]), capitalization of [PROPER_NOUNS], and number formatting ([NUMBER_STYLE]). Output the fully corrected text plus the issue log. Constraints: do not change style or word choice beyond errors; preserve the author's voice ([VOICE_NOTES]); flag anything that looks like an error but might be intentional ([INTENTIONAL_ITEMS]).

Review this draft for originality before publishing to [PUBLICATION_CHANNEL]: [PASTE_TEXT]. Run QuillBot's Plagiarism Checker and for each flagged passage report: the passage, the similarity percentage, the matched source ([SOURCE_URL] if shown), and whether it is a proper quote, a paraphrase needing citation, or common knowledge. Then use the Paraphraser in [MODE, e.g. Standard] to rewrite the passages that need rewording, and generate citations for the ones that need attribution via the Citation Generator in [CITATION_STYLE]. Constraints: do not delete cited facts; keep rewritten passages the same length (+/- 15 percent); final draft must pass a re-check.

QA this multilingual content package for [CAMPAIGN]: source text [SOURCE_LANGUAGE]: [PASTE_SOURCE]. Use QuillBot's Translator to produce [TARGET_LANGUAGE_1] and [TARGET_LANGUAGE_2] versions, then run the AI content detector on all three versions and report the scores. For each translation, verify: key terms ([GLOSSARY_TERMS]) translated consistently, brand name [BRAND_NAME] untouched, and tone matching [TONE_NOTES]. Flag any translation that reads machine-generated ([AI_SCORE_THRESHOLD] or above) for human review. Output: the translations, the detector scores table, and a list of terms needing a human translator's eye. Constraints: never translate [DO_NOT_TRANSLATE]; keep legal disclaimers ([DISCLAIMER_TEXT]) exact in meaning.