Qwen Prompts

Research [TOPIC] with web grounding. I need current facts as of [DATE] for [PURPOSE, e.g. a market entry decision, a thesis chapter]. Deliver: a 500 word brief with sections [SECTION 1], [SECTION 2], [SECTION 3], every factual claim backed by a cited source in the citation panel, key numbers in a table ([METRIC] by [YEAR OR REGION]), 2 expert viewpoints that disagree (attributed), and what remains uncertain. My lens: [YOUR ROLE AND REGION]. If Chinese language sources add value on [ASPECT], include them with translated summaries.

I am researching the Chinese market for [PRODUCT OR INDUSTRY]. Cover: market size and growth ([SEGMENT]), top [NUMBER] players with market share estimates, consumer behavior specifics on [PLATFORM: e.g. Douyin, Xiaohongshu, Taobao], regulatory requirements for [FOREIGN OR DOMESTIC] companies ([LICENSE OR RULE]), pricing norms in [CURRENCY], and 3 case studies of [SUCCESS OR FAILURE] with lessons. Ground this in Chinese sources (Baidu, Zhihu, WeChat articles) and translate key findings to [LANGUAGE]. Flag where data is thin or state influenced.

Translate this business document from [SOURCE LANGUAGE] to [TARGET LANGUAGE]: [PASTE DOCUMENT OR DESCRIBE LENGTH]. Type: [CONTRACT, PROPOSAL, EMAIL THREAD]. Requirements: preserve formatting and numbers exactly, use formal business register appropriate for [COUNTRY] business culture, keep these terms as defined: [TERM 1: DEFINITION], [TERM 2: DEFINITION], and add translator notes for idioms or culture specific references like [EXAMPLE]. After translating, back translate 3 critical sentences to verify meaning survived, and list any clause where nuance could shift legal interpretation.

I am uploading [FILES: e.g. a product photo, a scanned spec sheet, a chart image] related to [PROJECT]. Analyze across modalities: describe each image objectively, extract all text and numbers visible (flag anything unreadable), interpret the chart in [IMAGE] (trend, outliers, what the axes hide), and cross check the images against this text I provide: [PASTE TEXT]. Report inconsistencies between the visuals and the text, then answer [QUESTION 1], [QUESTION 2] for my decision on [DECISION]. Suggest what extra image ([WHAT]) would resolve the remaining ambiguity.

Task: [CODING TASK, e.g. build a REST API endpoint, write a data pipeline] in [LANGUAGE] using [FRAMEWORK]. Requirements: [REQUIREMENT 1], [REQUIREMENT 2], [REQUIREMENT 3]. Generate the code with clear comments, then self review it: list 3 potential bugs, 2 performance concerns for [SCALE], and 1 security issue to double check ([AREA]). Include unit tests for [FUNCTIONS] and a brief README section on how to run it. My environment: [OS, VERSIONS]. If a Qwen coder variant fits this task better, say which and why.

Act as my task assistant for this real world errand: [ERRAND, e.g. plan a team dinner, book travel legs]. Details: [DATE], [PARTY SIZE], [BUDGET], [CONSTRAINTS: dietary, location]. Steps: 1) find [NUMBER] options for [VENUE OR SERVICE] with ratings and prices, 2) compare them on [CRITERION 1], [CRITERION 2], 3) check availability signals, 4) draft the booking message or order in [LANGUAGE]. Confirm each step with me before proceeding to the next. If a step needs a real world action you cannot take (like a phone call), prepare exactly what I should say, including [KEY PHRASES].

I have [NUMBER, e.g. 100] documents of type [TYPE: invoices, resumes, contracts] to process. Design the extraction workflow: the exact fields to pull from each ([FIELD 1], [FIELD 2], [FIELD 3]), the prompt template to apply per document, validation rules ([RULE: e.g. dates must be YYYY-MM-DD, amounts positive]), how to handle failures (unreadable scan, missing field: mark [FLAG] never guess), the output table schema, and a quality sampling plan (manually verify [N] random docs). Then process the first 3 documents I upload as a pilot and report accuracy before we scale.

I want to track prices for [PRODUCT] across [RETAILER 1], [RETAILER 2], [MARKETPLACE]. My target price: [PRICE] in [CURRENCY]. Build me: a tracking table template (retailer, current price, shipping, seller rating, last checked), what counts as a genuine deal versus a fake discount on [PRODUCT] (typical price history pattern), 3 price alert rules ([RULE: e.g. alert below X, alert on coupon stack]), and red flags for counterfeit sellers of [BRAND]. Check current listings with web grounding and fill the table with today's prices and sources.

Help me write academically in [TARGET LANGUAGE: English or Mandarin] about [RESEARCH TOPIC]. My draft section: [PASTE DRAFT, up to 500 words]. Tasks: correct grammar and academic register, improve the argument flow (flag any logical leap between [PARAGRAPH A] and [PARAGRAPH B]), suggest 3 stronger topic sentences, check that citations ([CITATION STYLE]) are formatted correctly, and explain each major correction so I learn. My field: [FIELD], target venue: [JOURNAL OR CONFERENCE]. If a term has a standard [CHINESE OR ENGLISH] equivalent, use it consistently.

I am uploading [NUMBER] product images: [DESCRIBE: e.g. three jackets I am choosing between, a gadget from different angles]. For each: describe objectively (material cues, construction quality signals, branding), estimate the likely price tier and why, flag anything that looks off ([COUNTERFEIT SIGNS, QUALITY RED FLAGS] for [PRODUCT TYPE]), and compare them for my need ([MY USE CASE]). Then search the web for the actual product listings, match each image to a listing with price, and tell me which is the best value under [BUDGET]. Note where the photo may be misleading ([LIGHTING, ANGLE] tricks).