Analyze a system prompt for context engineering issues and get top findings ranked by severity. Use for reviewing, improving, or debugging AI agent prompts.
MIT
204,350 tools. Last updated 2026-06-15 00:11
"Understanding Prompts or Prompt Engineering" matching MCP tools:
- Retrieve prompts from LangSmith with options to filter by visibility and limit results for prompt management.MIT
- Create a new prompt collection to organize prompts by app, establishing a namespace before adding prompts. Returns collection id and slug.MIT
- Lists prompt templates for engineering reasoning workflows, enabling structured thought through step-by-step reasoning, branching, merging, and validation.Apache 2.0
- Idempotently create or update a prompt for CI/CD and prompt-as-code workflows. Finds existing prompts by name within a collection and uses dry_run for safe preflight checks.MIT
- Discover available prompt engineering techniques with acceptance statistics to enhance AI interactions through optimized method selection.MIT
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Generate answers & visualizations from your engineering data to track software development health.
- Transform prompts using engineering best practices to improve clarity and effectiveness for AI assistants.MIT
- Improve prompt quality by applying optimal engineering techniques like chain-of-thought reasoning based on intent analysis.MIT
- Ask clarifying questions to understand user requirements and refine prompts for Claude Code engineering.MIT
- Provide answers to clarifying questions to continue prompt engineering for Claude Code, enabling interactive refinement of optimized prompts.MIT
- Combine multiple existing prompts into a single prompt to create complex multi-step workflows. Use search_prompts first to find prompt names, then compose them with custom separators.
- Explore available prompt categories and their prompt counts to understand the library structure before searching or creating prompts.
- Get guidance on using Smart Prompts tools effectively, including usage instructions, practical examples, and best practices for prompt management.
- Submit feature requests, report documentation gaps, or escalate issues to the engineering team through a direct email.ISC
- Generate structured prompt templates from feature requirements or existing prompts to enable systematic testing and evaluation of AI applications.Apache 2.0
- Save, run, list, or delete reusable prompt templates with {{variable}} substitution for use across AI assistants.MIT
- Retrieves task prompts with descriptions and technical data from Webvizio MCP Server to facilitate proper understanding and execution of development tasks when provided with a task UUID.MIT
- Statically analyze system prompts for prompt-injection vulnerabilities: identify untrusted placeholders, missing delimiters, dangerous instructions, and precedence inversion.MIT
- Analyze codebases and design user interfaces using Google Gemini's visual understanding and detective capabilities for rapid prototyping and comprehensive analysis.MIT
- Retrieve a prompt version by its identifier, optionally specifying a tag or version ID to target a specific version.Apache 2.0