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.
Rewrites awesome-cursorrules' Next.js App Router standard into an AGENTS.md/CLAUDE.md you can drop straight into your project root, so Claude Code, Codex, and Cursor automatically follow Server-Components-first, file-based routing, TypeScript, and performance conventions when writing Next.js.
Rewrites awesome-cursorrules' FastAPI production architecture standard into an AGENTS.md/CLAUDE.md that enforces Router→Service→Repository layering, thin handlers, an anti-corruption layer, and idempotency — so AI automatically rejects anti-patterns when writing Python backends.
Rewrites awesome-cursorrules' Go backend scalability standard into an AGENTS.md/CLAUDE.md covering idiomatic error handling, context propagation, interface abstraction, concurrency, and observability — so AI follows standard conventions and trade-off analysis when writing Go services.
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 mcp-builder: a four-phase workflow (research & planning → implementation → review & testing → writing evals) for wrapping your API or service into a high-quality MCP server. Covers both Python (FastMCP) and TypeScript (MCP SDK), with emphasis on tool naming, input/output schemas, error messages that point toward a fix, and evaluating with real-world tasks.
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.'
Uses two Markdown templates (create-prd.md and generate-tasks.md) to turn 'dumping a pile of requirements on AI' into a controlled process: first generate a PRD, break it into a checkable task list, then complete one subtask at a time — pausing after each for your go-ahead before continuing.
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.
Uses VoltAgent/awesome-claude-code-subagents (154+ subagents, 10 categories, MIT license) as a curated directory for picking the right subagent and installing it into Claude Code's .claude/agents/ using the standard YAML format.
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.
A curated, ready-to-use version of OneRedOak's design-review workflow: using Playwright MCP in a real browser environment, it automatically audits frontend changes across 7 stages (interaction, responsiveness, visuals, accessibility, robustness, code health) and reports findings graded Blocker/High/Medium/Nitpick.
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.
Borrows the approach from the 40k-star awesome-cursorrules repo to codify 'how to write for a given tech stack' into a project rule file, so Cursor / Claude Code / Codex always produce code in your conventions instead of generic boilerplate.
Has Claude Code scan your repo and produce a tight, verifiable CLAUDE.md project memory file under 200 lines—covering build/test/lint commands, directory structure, conventions, and prohibitions—while routing anything that doesn't belong there into skills or path-scoped rules instead.
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.
Uses hooks in .claude/settings.json to automatically run formatting, linting, type-checking, or tests at specific Claude Code lifecycle events (PostToolUse after an edit, PreToolUse before running a command, Stop when wrapping up)—producing correct JSON config plus an executable hook script, with exit code 2 hard-blocking dangerous actions.
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.
Has Claude Code break a large task into several independent, parallel subagents (each with its own context, restricted tools, and an assignable model), planning how to fan the work out, defining each subagent's responsibility boundaries and reporting format, and producing reusable .claude/agents subagent definition files when needed.
Applies the spirit of Plan Mode so Claude Code hands over a structured plan (files affected, steps, risks, acceptance criteria) before touching any file—you review, correct, and approve it before execution begins. Prevents the AI from charging ahead and writing a pile of things you didn't want.
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.