1328 hand-tested AI prompts across image, video, and music — each with full context, variables, and a sample output. Content is authored in Traditional Chinese; the UI here is English.
Doesn't let the AI just hand in its answer as-is: it first tags the source type of every key sentence, then hunts for counterexamples to attack its own claims, and finally grades confidence level item by item with suggested directions for verification. Good homework before researching, writing a report, or making a decision. Honest note: this isn't the same as actual fact-checking (the model may not be able to search the web) — but it forces uncertainty out into the open and noticeably reduces confident-sounding nonsense.
Report a bug in this format and the AI's fix hit rate jumps noticeably: give all four parts at once — the raw symptom, a minimal repro, expected behavior, and environment — and force the AI to diagnose first, ask for more information when it's insufficient, and never guess-and-change blindly. Suited to any scenario where you're asking ChatGPT or Claude to fix code. Note: the AI's diagnosis is reasoning, not an actual test run — after the fix, be sure to actually run through the included verification checklist.
Feed in a lease, employment, or outsourcing contract, and it scans clause by clause from your side of the deal: a plain-language translation, worst-case scenario, risk grading, and negotiation angle for each, plus three questions to bring to a professional at the end. Note: this is a prep tool for understanding a contract, not legal advice — for high-value contracts or ones involving major rights, consult a lawyer, and it's safest to treat the scan results as homework to do before meeting one.
Did your boss just say "take a look at this" and walk off? Paste in the exact wording and context, and the AI breaks down the possible interpretations, key clarifying questions, and a draft confirmation message — so you align on direction before starting work, instead of wasting a whole week on the wrong thing.
Don't publish AI-written copy as-is: run it through three rounds of checks to catch hallucinated data, fabricated sources, and outdated information, with each item graded as trustworthy, needs your own verification, or needs a rewrite — comes with a reusable pre-publish checklist.
Feed the AI the background of a matter and it produces a draft following Taiwan's official document format — Subject, Explanation, Action — automatically applying standard bureaucratic phrasing and adjusting tone for upward, lateral, or downward correspondence. The final section forcibly flags regulations and figures that "need human verification"; this is positioned as a draft, not a final document.
Bilingual Chinese-English localization with one more layer than Google Translate. Specifies Traditional Chinese as used in Taiwan plus Taiwan-specific idioms, keeps names, brand names, and technical terms from being mistranslated, and delivers both a literal version and a localized, polished version in one pass so you can compare and pick. You can also feed it style samples so it learns your company's tone. Suited to marketing copy and product descriptions for foreign firms, freelancers, and cross-border e-commerce in Taiwan.
The 2026 cognitive gap: reasoning models like Opus, GPT-5, and Gemini Deep Think already think internally, so 2023-era incantations like 'you are a top expert,' 'take a deep breath,' and 'let's think step by step' are ineffective on them — or even counterproductive. This prompt has the AI rewrite your old prompts into a reasoning-model version, with a before/after comparison table, and explains which models count as reasoning models and whether free tiers support them.
A no-code way to run Self-Consistency: have the AI solve the same problem via three different lines of reasoning, then compare the results and take the majority consensus. Especially useful for scenarios where a mistake is costly — tax estimates, loan interest comparisons, recipe scaling. Worth noting upfront: this uses more tokens, so it burns through free quotas faster.
A workflow mindset office workers can copy directly. Complex tasks (writing a proposal, building a report) done in one giant prompt come out poorly; this teaches you to split it into four steps — outline → expand each section → proofread and polish → convert to bullet points — with the output of each step feeding the next, plus four ready-to-use Traditional Chinese prompts. You can even change direction mid-task by rerunning just one step instead of starting over.
A reusable Traditional Chinese 'prompt optimizer' incantation — paste in a rough prompt and it first asks for the key missing details, then produces a well-structured version along with notes on what changed and why. Honestly flags its limits: a meta-prompt can fix structure and phrasing, but not factual errors in the content itself.
A turn-based mock interview: the interviewer asks scenario-based questions tailored to your industry, one at a time, follows up on your answer before giving feedback, and provides a speakable English version of the answer for each question. After eight questions, you get an overall hiring-likelihood assessment. Closer to a real interview than just reading past questions.
For a boss's urgent demands, pushback, or last-minute extra work, this first diagnoses what they actually need (reassurance? a scapegoat? just an update?), then gives short, full, and escalation-ready reply options with risk notes for each. Built-in red-line check: it refuses goals that would require lying and offers an honest alternative instead.
The worst part of writing a year-end self-review is not being able to remember what you did all year, and then having it come out reading like a diary log anyway. This prompt lets you dump in a whole batch of weekly reports, calendar events, or scattered notes, and the AI organizes them into 3-5 achievement themes, fills in quantified phrasing, and aligns everything with company goals to produce a formal self-review. It also includes a "raise negotiation" version you can use directly when discussing salary.
When you're assigned to run training or onboard new hires, the time-consuming part isn't knowing the content — it's arranging it into an order you can actually teach. This prompt uses the basic instructional-design framework (objectives, motivation hook, explanation, practice, assessment) to produce a complete lesson plan, including time allocation, interaction design, and points where learners tend to get stuck. Works for corporate training, new-hire onboarding, and club/community teaching.
Converts plain-language requests like 'find customers who bought more than 3 times last month' into an executable SQL query plus an explanation — give it your table schema for even more accurate results.
Hand the AI the options you're torn between; it lists the key considerations, gives weighted scores, points out risks you might have missed, and gives a reasoned recommendation.
For emailing strangers: one line of relevant opening, one line naming their pain point, one line of concrete value, and one low-friction CTA — avoiding the 'our company was founded in...' dead-on-arrival opener.
Generate a full sales-page copy skeleton in one shot: an attention-grabbing headline, amplified pain points, stacked benefits, objection handling, and a strong CTA — ready to drop your product straight in.
Generates 5 title-plus-thumbnail-text combinations for a single video — the title creates curiosity, the thumbnail adds non-redundant information, and together they drive more clicks than either alone.
Gives you a response script for each of the most common customer objections — not a hard pitch, but 'acknowledge first, then reframe' — phrased naturally so it doesn't sound rehearsed.
Have AI review your code like a senior engineer: it flags concrete issues and fixes across four dimensions — correctness, security, performance, and readability — instead of vague praise.
Has the AI produce a first draft, then switch into a strict editor role to pick apart its own flaws, and finally rewrite based on that critique — effectively running three rounds of polish inside a single prompt.
Write out the grading rubric in your head and give it to the AI first — it will use that yardstick to self-align, self-evaluate, and fix whatever falls short, getting you much closer to the quality you actually want.