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.
Has Codex do a disciplined code review of your git diff across three tracks (correctness bugs / simplification-and-reuse / security), listing each finding with a confidence level and a pastable fix, and explicitly instructed to say so when nothing's wrong instead of manufacturing complaints.
Forces Codex through a closed loop — write a failing test that reproduces the bug, find the root cause, make the minimal fix, watch that same test go from red to green, then run the full test suite to confirm no regressions — eliminating both 'fixed it without verifying' and 'changed a bunch of unrelated stuff along the way.'
Has Codex write characterization tests for untested legacy code: it first reads and documents what the code 'actually does right now' (bugs included), systematically covers the happy path plus edge cases and error paths, and is strictly forbidden from modifying the code under test.
Has the agent automatically inventory your Cursor project (.cursorrules, .cursor/rules, .cursor/mcp.json), produce a step-by-step migration plan, and generate the corresponding CLAUDE.md or AGENTS.md, slash commands, and MCP config — so you're not stuck 'dumber than Cursor' on day one.
A Definition of Done template you can paste into any coding agent, turning 'what counts as done' into a checklist the agent must self-verify item by item: behavior meets acceptance criteria, tests/lint/typecheck/build all pass (or it states why they didn't run), risky changes come with a rollback plan, and a final 'verification story' is delivered. Puts an end to agents claiming 'done' while everything is actually broken.
A large-refactor playbook for agents: first do a read-only survey of the 'blast radius' — which files, call sites, and tests are affected — then split the change into small batches, each preserving behavior, each run through its own tests, each its own atomic commit. Puts an end to 'change 40 files at once, then the build breaks and no one knows where to start fixing it.'
No need to memorize regex syntax — describe in plain language what you want to match, and the AI gives you the regex, an explanation of what each part does, and test cases.
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.
Use the Feynman Technique to have AI teach you: first explain it clearly in plain language with an analogy, then flag the point you're most likely to misunderstand, and finish with a self-check.
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.
Ad testing creative for Facebook / Google: generate 10 headlines from different angles (curiosity, numbers, pain points, contrast, urgency...) at once, ready for A/B testing.
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.
The new traffic battleground in 2026 is getting cited by AI. Write your topic in the format AI models love to pull from: direct answers, clear structure, and authority signals.
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.
A complete faceless short-video script: a 3-second hook, value in the middle, a CTA at the end, with voiceover plus shot descriptions ready to pair with AI-generated video.
Rewrites a long article / blog post / report into a 6-9 post thread for X or Threads: the first post as the hook, one point per post, and a CTA at the end.
2026 has entered the agent era — this template turns 'I want X' into an executable spec for an agent: goal, steps, available tools, definition of done, and boundaries.
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.
Building a personal brand doesn't mean racking your brain for a new angle every day — give it one topic, and it produces 5 social posts from different angles (story / opinion / how-to / contrast / interactive) in one go.
Turns a messy meeting transcript or notes into decisions, action items (owner + deadline), and open questions — done in 30 seconds after the meeting.
Feed the AI structured background, what's already been tried, constraints, and available tools/data structures before giving it the task — in 2026 the real leverage point has shifted from 'prompt tricks' to 'context.'
Don't feed an entire complex task into a single prompt — split it into three separate steps ('decompose → produce each part → integrate'), and the output is noticeably more stable and complete.