prompts.chat
claudeAccess thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
2 skills · 2 commands · 2 agents · 1 MCP server
Build and manage ChatGPT Workspace Agents from Claude Code by driving the agent builder in a browser (no public API exists).
Plugin chatgpt-agent-builder from marketplace chatgpt-agent-builder in danielrosehill/ChatGPT-Workspace-Agents-Claude-Plugin. Commands read from the repo's manifest — 5 days ago.
create-agentCreate a new ChatGPT Workspace Agent (ChatGPT Business / Enterprise / Edu) by driving the agent builder at chatgpt.com/agents/studio in a signed-in browser. Sets the name, instructions, context files, skills and apps, then saves with Create. Use on "make a ChatGPT agent for X", "create a workspace a
inspect-agentRead the current state of one ChatGPT Workspace Agent from the browser builder, without changing anything. Covers name, instructions, files, skills, apps, sharing and schedules. Use on "what's in agent X", "show agent X's instructions", "which skills does agent X have", or before update-agent.
list-agentsList the ChatGPT Workspace Agents you can see (Built by me, Recently used, or the workspace directory) with their names and agt_ IDs, read from chatgpt.com/agents in the browser. Use on "what ChatGPT agents do I have", "list my workspace agents", "find the ID of agent X".
share-agentChange who can use or edit a ChatGPT Workspace Agent (private, anyone in the workspace with the link, or listed in the workspace directory), or invite named people as Can chat / Can edit / Owner, through the builder in the browser. Use on "share agent X with Y", "list agent X in the directory", "mak
update-agentChange an existing ChatGPT Workspace Agent in the browser builder. Replace or edit its instructions; add, replace or remove skills and context files; add or remove apps; rename it; then save with Update. Use on "update agent X's instructions", "add these skills to agent X", "replace the skill on X",
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
2 skills · 2 commands · 2 agents · 1 MCP server
Dedicated ChatGPT Federation MCP publisher with isolated Nostr signing-key custody, OAuth-scoped publishing, and signed public-channel coordination over the Ruflo relay. As a mod (ADR-445 pattern): a tighten-only tool guard, a local slash command, and a status file the console shows.
Personalized AWS guidance built on patterns from 350,000+ startups. Get architecture, cost, and security recommendations matched to your stage, from day-one account setup to production-ready infrastructure. Migrate to AWS from Azure, GCP, or Heroku with resource discovery, cost estimates, and generated Terraform. Move OpenAI, Azure OpenAI, and Gemini code to Amazon Bedrock, and plan and prototype AI agents on AgentCore and other AWS runtimes. Includes AWS Activate credits eligibility, 60+ exclusive startup offers, and multi-account, multi-region support. Built by AWS Startup Solutions Architects.
13 skills · 1 command · 7 agents · 1 MCP server
Independent auditing for AI agents, open source. Claude discovers your setup, confirms the cost, and audits your agent against the one question other tools skip: is it doing the job it's supposed to do, given your business rules and org structure? Test any model (Anthropic, OpenAI, Gemini, Azure, Bedrock, …) graded by self, one independent judge, or a cross-vendor panel; each provider is billed to its own account via a key in your settings, never the command line. Results render as an interactive artifact (with a static-report fallback).
1 skill · hooks
Cross-platform ad management for Google Ads, Meta Ads, TikTok Ads, and LinkedIn Ads. 91 tools for keyword research, campaign creation, performance analysis, and budget optimization.
15 skills · 5 commands · 1 agent · 1 MCP server
Knowledge base compiled from OpenAI's Spinning Up in Deep RL (MIT, Joshua Achiam) by engineering/book-to-skill. A resident core carries the RL optimization problem, the model-free taxonomy, the policy-gradient template with its five valid weights, the safe-step family (VPG to TRPO to PPO) and the overestimation family (DDPG to TD3 and SAC); 20 on-demand chapters cover key concepts and MDPs, the algorithm taxonomy and model bias, the policy gradient derivation with the log-derivative trick and EGLP lemma, Achiam's researcher essay, the key-papers topic map, the exercises including the silent DDPG broadcasting bug, the benchmark parity disclosure, one chapter per algorithm, and the logger/MPI/ExperimentGrid utilities. Ships a glossary, a patterns file with 16 techniques, a decision cheatsheet with thresholds, a cs-spinning-up-deep-rl agent and /cs-spinning-up-deep-rl. Structured study notes, not a reproduction of the source.
1 skill · 1 command · 1 agent
This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.