Results for “promptfoo”

Manage golden dataset regression tests for LLM prompts using Promptfoo. Includes setup, test case capture, repeatable runs, and reports. Use after changing prompts or when checking for prompt regressions.

"Set up Promptbook \u2014 connect your account to start tracking builds.\n\ Use when the user wants to enable session analytics on promptbook.gg.\nTrigger with\ \ \"/setup\" or \"set up promptbook\".\n"

Generates optimized prompts for any AI tool. Use when writing, fixing, improving, or adapting a prompt for LLM, Cursor, Midjourney, image AI, video AI, coding agents, or any other AI tool.

Expert prompt optimization for LLMs and AI systems. Use PROACTIVELY when building AI features, improving agent performance, or crafting system prompts. Masters prompt patterns and techniques.

Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates with evals.

Transforms vague UI ideas into polished, Stitch-optimized prompts by enhancing specificity, adding UI/UX keywords, injecting design system context, and structuring output for better generation results.

Estrutura prompts para geradores de imagem e vídeo, otimizando custo e consistência com a marca.

Expert prompt optimization system for the prompts INSIDE an AI product you are building — system prompts, LLM feature prompts, chatbot/agent instructions. Use when the user wants to write or improve a system prompt for an AI feature they're shipping, review/critique an LLM prompt, apply prompt-engineering techniques (chain-of-thought, few-shot, structured output, hard constraints) to a product prompt, or optimize cost/latency of a production prompt. Do NOT use this to clarify or structure the user's own vague request to Claude Code — that is `prompt-clarifier`'s job, not this skill's.

Derive a portable product-idea kickoff prompt from the invoking repository for use with $idea-scope-brief in a different repository. Use when a repo suggests an adjacent product, SaaS, devtool, library, workflow, or experiment worth briefing elsewhere, but the user wants an idea prompt rather than code extraction or repo creation.

Silently restructures natural-language prompts into the format best suited for the model currently executing the skill, then answers the rewritten version.

A library of reusable, production-tested prompt engineering patterns for building AI-powered features. Use when designing system prompts for apps, building AI pipelines, selecting the right prompting technique for a use case, or reviewing prompts for common failure modes. Complements the prompt-engineering skill (which covers the optimization framework); this skill covers the pattern library itself.

Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.

Transforms vague UI ideas into structured, Stitch-optimized prompts with design system context and UI/UX keywords.

Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design.

Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.

Meta's 86M prompt injection and jailbreak detector. Filters malicious prompts and third-party data for LLM apps. 99%+ TPR, <1% FPR. Fast (<2ms GPU). Multilingual (8 languages). Deploy with HuggingFace or batch processing for RAG security.

Discovers and applies curated prompts from the prompts.chat collection to optimize AI interactions, prompt engineering, and workflow integration.

Designs, optimizes, and evaluates prompts for LLMs, including structured outputs, chain-of-thought, and evaluation frameworks.

Activates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.

Researches conversation and code context to generate 1-6 targeted clarifying questions when a prompt is vague, then executes the original request.

Enriches vague, low-detail prompts into structured, agent-optimized XML before execution. INVOKE IMMEDIATELY — before any tool use or file reads — when you detect any of these signals: prompt under 10 words with no file path or error message; vague action verbs with no object ("fix the bug", "make it better", "clean this up", "refactor this", "optimize performance", "improve the UI", "add authentication", "add payments", "add notifications", "build the feature"); CLARIFIER_ADVISORY in your context window; user says "clarify", "help me describe this", "enrich this prompt", "structure my request". Also triggers on: "make this work", "it's broken", "it looks bad", "add X" with no further detail, "implement Y" with no constraints. Do NOT trigger on: prompts ending with ?, prompts containing error messages or stack traces, prompts with specific file paths, prompts already containing acceptance criteria or success metrics.

Designs and optimizes prompts for LLM-powered applications, covering system prompt architecture, context management, output formatting, and evaluation.

Prompt Summary - rigorous, review-ready analysis of any AI prompt

Start voice calls via the Clawdbot voice-call plugin.

Expert photography prompt engineer specializing in crafting detailed, evocative prompts for AI image generation. Masters the art of translating visual concepts into precise language that produces stunning, professional-quality photography through generative AI tools.

Design a learning sequence teaching prompt quality — comparing vague vs. refined prompts to show why specificity and context transform AI output. Use when students use AI without understanding why output quality varies.

Learn best practices for writing effective AI video generation prompts, covering shot types, camera movements, lighting, style keywords, and model-specific tips for Veo, Seedance, Wan, Grok, and others.

Generates a complete Figma Make prompt package with context primer, checkpoint, build prompts, and iteration templates for designing UI pages, components, or screens.

Configures autonomous heartbeat and cron-based proactive routines (e.g., morning briefing setup, unanswered-message scan cadence). Invoke when user is SETTING UP or MODIFYING a proactive routine, not when the routine itself fires. Cron crons execute their own logic — they do NOT load this skill. Triggers: "set up proactive check", "configure heartbeat", "add morning briefing", "tune cron cadence".

Create a working customer profile from existing research, market signals, and team knowledge before deeper validation.

Deno reference tool. Use when working with deno in frontend contexts.

gRPC service development. Protocol Buffers (protobuf), service definitions, streaming (unary, server, client, bidirectional), interceptors, and code generation for Node.js, Go, Java, and Python. USE WHEN: user mentions "gRPC", "protobuf", "Protocol Buffers", ".proto", "grpc-js", "tonic", "grpc-java", "service mesh RPC" DO NOT USE FOR: REST APIs - use `rest-api`; GraphQL - use `graphql`; WebSocket - use real-time skills

Detect prompt injections and jailbreak attempts in LLM applications using Meta's 86M parameter classifier. Filter user inputs, third-party data, and RAG documents with low latency and multilingual support.