Generate AI writing suggestions for revision, next steps, or alternatives based on a prompt or document content.
AGPL 3.0
260,827 tools. Last updated 2026-07-05 08:29
"A tool or resource for improving prompt writing" matching MCP tools:
- Get structured guidance for writing prompts that produce optimal video generation results. Includes examples and tips for effective prompt structure.MIT
- Packages the synthesis context from the synthesize_memories prompt into a tool result for clients with limited prompt capacity.MIT
- Start a structured workflow to write or improve test coverage. Provide a task description and optionally specify target files, test type, framework, and coverage goals.MIT
- 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
- Run large language models from Replicate for text generation, Q&A, code writing, summarization, translation, and more. Tune output with customizable model, temperature, system prompt, and generation limits.MIT
Matching MCP Servers
- Alicense-qualityAmaintenanceEnables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.Last updated221MIT
- Alicense-qualityDmaintenanceEnables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.Last updatedMIT
Matching MCP Connectors
1,177 free agentic trading prompts for Claude and Robinhood MCP.
Search the AI Tool Directory catalog: tool details, status checks (alive/acquired/deceased + cause and date), alternatives, and side-by-side comparisons. Read-only.
- Create a test factory that generates valid resource instances with sensible defaults and faker-based realistic values, reducing boilerplate in test setup.MIT
- Retrieve a complete fix context for a single bug report: plain-English diagnosis, reproduction steps, root cause, blast radius, and fix prompt. Use before writing a fix.MIT
- Retrieves KQL query examples matching your prompt to reveal correct databases, tables, and column names for writing accurate queries.MIT
- Generate structured prompt templates from feature requirements or existing prompts to enable systematic testing and evaluation of AI applications.Apache 2.0
- Search PatternFly resources by name or partial match to get component names, documentation URLs, and resource URIs.MIT
- Generate or modify code files with smart diffs. Provide file path and detailed prompt to create or edit files using context for accurate code generation.MIT
- Detach a tag from a resource without deleting the tag or resource. Idempotent operation ensures safe repeated use.Apache 2.0
- Generate a 3D mesh from a text prompt or reference image. Choose from curated models like Hunyuan-3D, Rodin, or TripoSR to create GLB/OBJ files.MIT
- Attach a resource (text or file) to a task within the same project. Use for release notes, design docs, or references; call once per task for multiple tasks.MIT
- Preview a redacted external handoff receipt from the agent marketplace without writing or paying.MIT
- Fetch a prompt version by identifier; optionally specify a tag or version ID to get a specific version.Apache 2.0
- Prepare a session to accept or dismiss the next JavaScript dialog (alert, confirm, or prompt) with optional prompt text. Call this before the dialog-triggering action to prevent timeout.AGPL 3.0
- Assign a resource to a node's property, either by loading an existing resource from a res:// path or minting a new inline sub-resource of a specified class.MIT
- Compare a trader's 30-day performance to all-time results: PnL, trade count, win rate, and trend direction to determine if they are improving or cooling off.MIT