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
666,706 tools. Updated 2026-10-16 19:55
"Understanding Prompts or Prompt Engineering" matching MCP tools:
- Deletes an empty prompt group from the active project. Move any prompts first, because deletion cannot be undone.MITDestructive
- Audit tracked prompts to get intent, realistic metrics, play, and keep/cut/rewrite recommendations for each prompt.MIT
- Retrieve prompts from LangSmith with options to filter by visibility and limit results for prompt management.MIT
- Run multiple generation prompts in sequence with a shared system prompt. Captures errors inline per item, returning all results with delimiters.MIT
- Manage versioned LLM prompts by listing, reading, or activating stored prompt versions. Activating a version deactivates others for the same task.MIT
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- List all prompts exposed by a connected MCP server, including names, descriptions, and argument schemas, to enable accurate prompt invocation.MIT
- List prompt categories with prompt counts to pinpoint the right category before fetching saved prompts.MIT
- Detects hidden prompt injection in tool descriptions: file read, exfiltration, instruction override, system prompt extraction, social engineering. Returns findings with pattern and severity.MIT
- Recommends the retrofit level for an existing prompt or SKILL.md using the intent-engineering framework's blast-radius, complexity, and autonomy criteria.MIT
- List available LCV Ultrabrain prompt templates for common engineering reasoning workflows, enabling structured thought through step-by-step reasoning, branching, merging, validation, and quality metrics without external LLM APIs.Apache 2.0
- Enumerates MCP resources and prompts to flag broad URI patterns, sensitive paths, and social engineering risks.MIT
- Generate AI images from text prompts. Provide up to four prompts and choose an aspect ratio; each prompt yields one image.MIT
- Discover available prompt engineering techniques with acceptance statistics to enhance AI interactions through optimized method selection.MIT
- Retrieve prompts from the prompt library with optional name filter and pagination. Manage your prompt collection without using the web UI.MIT
- Inspect the prompt templates this project uses and where each comes from (shipped, project override, or config path). `get` renders a workflow command or macro as prompts/get does; `eject` copies the shipped ones into .ddflow/prompts/ to…MIT
- 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
- List saved prompts from your Pretty Prompt library. Search, filter by favorites, and paginate to find the prompt you need.MIT
- Transforms user requests into optimized prompts using advanced prompt engineering techniques like chain-of-thought and role-based prompting.MIT
- Fetch LangSmith prompts by visibility and limit, returning prompt metadata for collection management.MIT