inferen-sh

Structured agent responses often need a consistent interactive interface. This skill maps widget data into React layouts, controls, forms, and action events.

Current information is difficult to gather and compare manually. This skill runs Tavily and Exa through inference.sh for search, extraction, and sourced answers.

Managing repetitive X actions manually consumes time and creates inconsistent workflows. This skill provides belt CLI commands for posts, media, engagement, messages, follows, profiles, and deletions.

Agent applications need clear feedback for tool calls, approvals, and results. This skill provides React patterns for presenting each lifecycle state consistently.

Turning React animation code into shareable video requires a rendering pipeline. This skill submits Remotion components to inference.sh and returns rendered video output.

Text-heavy image prompts often produce weak layouts and unreadable lettering. This skill guides Qwen-Image-2.0-Pro generation and editing through inference.sh.

Python teams need clear SDK guidance for AI apps, agents, streaming, files, and sessions. This skill gives Codex, Claude, and Claude Code practical patterns for inference.sh.

Creating polished images and text-heavy graphics often requires several tools. This skill runs Qwen-Image-2 models through inference.sh for generation, editing, and controlled output.

Local environments may lack the libraries or resources required for Python tasks. This skill sends workloads to a hosted CPU sandbox with common packages.

Creating video model commands requires choosing compatible inputs and settings. This skill guides Pruna P-Video and WAN generation through the inference.sh CLI.

Image teams need fast generation and editing across several visual workflows. This skill runs Pruna P-Image models through the inference.sh belt CLI.

Creating polished images often requires separate tools for generation, editing, and current information. This skill provides one inference.sh workflow for all three tasks.

Creating consistent images requires model selection and precise command inputs. This skill prepares and runs Gemini image workflows through the inference.sh CLI.

JavaScript teams need clear patterns for adding hosted AI tasks and agents. This skill provides SDK guidance for execution, streaming, files, tools, sessions, and proxies.

Using many hosted AI models from a terminal requires different app names, inputs, and task flows. This skill provides focused inference.sh CLI guidance.

Producing natural narration often requires manual setup across voice, model, and format options. This skill helps Claude, Codex, and Claude Code run ElevenLabs TTS through the inference.sh CLI.

Creators need original music without a full composition workflow. This skill helps Claude, Codex, and Claude Code prepare ElevenLabs music prompts through inference.sh.

Teams need chat interfaces that feel consistent with modern React applications. This skill provides reusable chat component patterns for React, Next.js, and shadcn-style projects.

Creating visuals across many AI image models can require separate tools and prompts. This skill gives Claude, Codex, and Claude Code concise inference.sh guidance for generation, editing, upscaling, and discovery.

Teams need fast access to many AI video models without learning every provider API. This skill gives Claude, Codex, and Claude Code concise inference.sh workflows.

React teams need agent interfaces that handle streaming, tools, approvals, and rich responses without custom infrastructure. This skill shows how to add a ready agent component, proxy route, and scoped tool patterns.

Teams need one way to run many AI models without managing GPUs. This skill guides Claude, Codex, and Claude Code through inference.sh CLI workflows.

Manual browser tasks slow research, testing, and evidence capture. This skill lets AI agents navigate pages, use element refs, capture screenshots, and run controlled browser workflows.