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.
Anthropic's official skill-creator: a meta-skill that "asks you clarifying questions, produces a SKILL.md, runs evals, refines the trigger description, and packages everything into a .skill file." It teaches you to build reusable Claude skills using a standardized directory structure and progressive disclosure.
Anthropic's official algorithmic-art skill: write an 'algorithmic philosophy' first, then turn it into an interactive HTML piece with p5.js. The core is Art Blocks-style seeded randomness (same seed = same image), paired with tunable parameters and seed navigation, letting you systematically explore generative art techniques like flow fields and particle systems instead of randomly flailing.
GitHub's official open-source tool for Spec-Driven Development. Using /speckit.specify → /plan → /tasks → /implement, it turns a vague requirement into an executable specification end to end, then has the AI generate code from that spec — fixing the unpredictability of 'vibe coding.'
Distills 14 classic software engineering books (Clean Code, Refactoring, Domain-Driven Design, The Pragmatic Programmer, Working Effectively with Legacy Code, and more) into imperative rule sets you can paste directly into AGENTS.md / CLAUDE.md / Cursor rules, offered in full / mini / nano sizes so you can pick based on your context budget.
Installs the flagship code-reviewer subagent from wshobson/agents (36k stars, MIT license) into Claude Code, giving you an Opus-powered senior reviewer specialized in security, performance, and maintainability that automatically takes over review after every commit.
Distills the open-source SuperClaude framework's /sc: command system and cognitive-persona mechanism into a ready-to-use workflow prompt, upgrading Claude Code from "one question, one answer" into a structured development process covering everything from brainstorming to implementation, testing, documentation, and version control.
Curates three core project-rules from steipete/agent-rules into a single rule pack usable directly as a slash command: semantic commits (12 types plus emoji, with automatic splitting into atomic commits), a 6-persona professional PR review, and 5 Whys root-cause analysis.
Turns the checklist or multi-step process you re-paste every time into a custom slash command (.claude/commands/<name>.md, or the newer .claude/skills), with correct frontmatter, $ARGUMENTS parameters, live context pre-injected via `!cmd` (git diff, PR content), and permissions scoped down with allowed-tools.
Has Claude Code interview you about a repetitive manual process, then produce a fully-structured Agent Skill (SKILL.md) covering name/description/trigger conditions/step-by-step instructions/acceptance criteria/supporting references, and verify it can be triggered automatically as well as invoked via a /slash command.
Has Claude Code help you connect an MCP server (a database, Notion, GitHub, your own API...), choosing the right transport and scope, using .mcp.json or claude mcp add, handling secrets and OAuth securely, and finally demonstrating how mcp__server__tool tools and @resource pull external data into your workflow.
Forces Claude Code through a strict red→green→refactor cycle: for every behavior, first write a test that fails (red) and actually run it to prove the failure, then write the minimal implementation that just makes it pass (green), and finally refactor under the safety of the passing tests. Cures the AI's old habit of jumping straight to the happy path, skipping edge cases, and faking test coverage.
Corrects Claude Code's tendency to 'see an error and start randomly editing' into a disciplined 4-step debugging process: reliably reproduce the bug first, isolate the true root cause (not just the symptom) through minimization, write a regression test that fails, apply the smallest possible fix, then run the full test suite to prove it's fixed without breaking anything else.
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.
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.