LLM Mart Trusted

A Claude skill that reviews a diff by trying to refute each finding before reporting it.

A prompt that forces Gemini to cite sources and flag uncertainty instead of guessing.

A workflow that makes DeepSeek state a hypothesis and a test before proposing any fix.

A Cursor recipe that writes a characterization test before each refactor step.

A skill that keeps a consistent persona and memory across a long MiniMax conversation.

Turns a staged diff into a clean Conventional Commits message — correct type, tight subject, useful body.

Uses ChatGPT search plus an adversarial verification pass to turn a fuzzy question into a sourced brief you can hand to someone else.

Forces Codex CLI to show the diff, review its own changes, run focused validation, and list uncertainty before you keep the patch.

A review skill that makes Copilot focus on concrete behavior changes, missing tests, and repo instructions instead of generic style chatter.

A starter layout for .github/copilot-instructions.md, path-specific instruction files, and AGENTS.md so Copilot stops guessing how your repo works.

Use /setupTests, /tests, and /fixTestFailure in a red-green loop instead of asking Copilot to “add some tests” and hoping for the best.

Forces a failing test that reproduces the bug before any fix — so you know it's actually fixed.

A reusable test harness for checking whether a custom GPT actually follows its instructions, uses tools correctly, and fails safely.

A structured security pass over a diff — checks the OWASP-relevant classes, ranks by exploitability, and shows a repro.

Stops the model from coding too early — lock a short spec and a test list before a single line is written.

The whole public catalogue is an MCP server and a REST API, so your agent can search skills, tools and slash-commands as native tools. Setup is one config block. Plus a private vault that carries your own prompts between machines.

You wouldn't ship a function you ran once. Here's the smallest evaluation setup that catches real regressions — five cases, three graders, and a rule for when to add a sixth.

AGENTS.md, CLAUDE.md, copilot-instructions.md and .cursor/rules all solve the same problem. Most of them are written badly. Here's what changes agent behaviour and what's decoration.

Sanitizing output protects your page. It does nothing for an agent that reads a poisoned README and then runs a command. A practical model of the threat, and what actually helps.

The words are used interchangeably and they shouldn't be. Six categories, what actually distinguishes them, and how to tell which one you're holding.

Most prompts are lucky one-offs. The ones that keep working share a structure: an explicit role, a checklist of constraints, a worked example, and a self-check step. Here's how to build one.

Enter shell mode to run commands.

Set a goal Claude keeps working toward across turns until it's met.

Configure Google Cloud Agent Platform authentication and model pins.

Reload a saved conversation from the session picker.

Build the structure of an article or document.

Show what's consuming the context window by category.

Configure your agent skills.

Export the current conversation as plain text.

Teach /run and /verify how to build, launch, and drive your app.

Switch Codex's communication style, such as friendly, pragmatic, or none.

Summarize with conclusions and clear action points.

Set limits on what the answer should or should not include.

Toggle max mode on the currently selected model.

Generate or update workspace instructions such as copilot-instructions.md or AGENTS.md.

Convert your repo's React design system and upload it to Claude Design.

Choose the default environment for cloud agents.

Show configured Model Context Protocol tools available in the session.

Explain a concept simply, pitched a step above ELI5.

Generate a prompt for an image or video model.

Toggle automatic command execution, or show its status.

OpenAI's general-purpose assistant for writing, research, coding, data analysis, and agentic tasks.

GitHub's AI pair programmer for inline suggestions, chat, agent mode, and code review across your editor and GitHub.

Anthropic's agentic CLI that edits code, runs tools, and ships changes.

The AI-first code editor — chat, edit, and refactor across your whole repo.