PROMPTS
1346 original and curated AI prompts across image, video, music, and tutorials. Browse by tool, use case, and difficulty; each entry shows its available notes and examples.
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Agent OS: Extract Codebase Standards and Auto-Inject into AI Agents
Borrowing the three-layer architecture from buildermethods/agent-os (Standards / Product / Specs): have AI first scan your codebase to extract existing conventions into documented standards, then auto-inject them every time it writes code — so you never have to re-explain the rules.
A Scalability-Focused AGENTS.md / CLAUDE.md Template for Go 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.
Codex config.toml in Practice: Approval Modes × Sandbox Isolation × Profiles
A ready-to-paste ~/.codex/config.toml template that sets up OpenAI Codex CLI's approval policy, sandbox isolation, reasoning effort, and multiple profiles in one go — balancing automation efficiency with safety boundaries.
Build Your Own Agent Skill Interactively with Anthropic's skill-creator
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 algorithmic-art Skill: Reproducible p5.js Generative Art
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.
OpenAI Codex's AGENTS.md: Rules for AI Written by a Real Large Project
A breakdown of the AGENTS.md actually in use in OpenAI's official codex repository — see how a project with millions of lines of code writes team conventions like formatting, testing, commits, module size limits, and API naming into an instruction file that an AI agent can understand and follow, plus a Traditional Chinese adaptation template you can apply directly to your own project.
GitHub Spec Kit: The Four-Stage Spec-Driven Development Workflow (/specify → /plan → /tasks → /implement)
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.'
agent-rules-books: Classic Software Books Distilled into AGENTS.md Rules
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.
wshobson's Flagship code-reviewer Subagent: A Senior Reviewer Inside Claude Code
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.
VoltAgent Codex Subagent Directory: Installing Specialist Agents via TOML in ~/.codex/agents
Uses VoltAgent/awesome-codex-subagents (166+ subagents, 13 categories, MIT license) as a Codex-equivalent curated directory, teaching you to define subagents in .toml format under ~/.codex/agents/ and invoke Codex subagents explicitly.
SuperClaude Framework: /sc: Commands and Cognitive Personas for Claude Code
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.
Agent-Rules Pack: Conventional Commits + 6-Persona PR Review + 5 Whys Root-Cause Analysis
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.
Claude Code Slash Command Designer: One-Click Custom /commands
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.
Claude Code Skill Factory: Turn Repetitive Workflows Into SKILL.md
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.
Claude Code + MCP: Connect External Tools to Your Dev Agent Safely
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.
Claude Code TDD Loop: Red, Green, Refactor Done Right
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.
Claude Code Bug-Fix Loop: Reproduce, Isolate, Fix, Verify
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.
Codex's Four-Gate Kickoff: Define the Task → Review the Plan → Check the Diff → Nothing Counts as Done Without Verification
Turns a vague requirement into a full Codex workflow: first force it to nail down a 'definition of done,' use plan mode to produce a plan for your approval, then implement in small steps, run its own tests, and finally produce a reviewable diff with verification evidence.
Codex Wrap-Up Officer: Turn Finished Changes into a Semantic Commit + a PR That Passes Review
Once your code changes are done, have Codex read the staged diff, produce a Conventional Commits message, and write a PR description covering background, what changed, why, how it was verified, and risks — without bundling in unrelated changes, exaggerating, or fabricating tests.
Codex Rigorous Diff Reviewer: Correctness, Simplification, and Security in Three Tracks
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.
Codex Bug-Fix Closed Loop: Reproduce First, Fix Second, With Rerunnable Verification
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.'
Codex Characterization Tests for Legacy Code: Lock In Current Behavior, Target Edge Cases, Zero Behavior Changes
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.
Migrating from Cursor to Claude Code / Codex: An Inventory-and-Kickoff Prompt
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.
AI Agent Definition-of-Done Self-Check Spec
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.