Results for “prompt-pack”

Analyzes draft prompts, identifies intent and gaps, matches ECC components, and outputs an optimized prompt for the user to paste and run. Advisory only, never executes the task.

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

Refines and polishes prompt files by applying proven best practices for structure, wording, and clarity while preserving original intent and formatting.

Creates, lists, retrieves, versions, and deletes managed prompts in Google Cloud Agent Platform using the Python SDK.

Learn and apply prompt engineering techniques for LLMs, image generators, and video models using the inference.sh CLI.

Analyze draft prompts to identify intent, scope, and missing context, then generate an optimized prompt with ECC component recommendations. Advisory only — never executes the task.

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

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

Test LLM applications for system prompt leakage using manual payloads, garak, and Promptfoo to extract embedded secrets and routing logic.

Detect and defend against prompt injection hidden in documents, web pages, and images consumed by an agent.

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

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.

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