belt

name: belt description: "Use the belt CLI — run 250+ AI apps, manage knowledge, search skills, connect MCP servers" allowed-tools: Bash(belt *)

belt cli

belt is the cloud platform cli for ai agents. single ~4mb binary, no runtime dependencies.

install

curl -fsSL cli.inference.sh | sh
belt login
belt me

apps — run 250+ ai models

belt app search "image"                      # find apps
belt app get openai/gpt-image-2              # view schema
belt app sample openai/gpt-image-2 --save in.json  # generate sample input
belt app run openai/gpt-image-2 --input in.json    # run it
belt app run openai/gpt-image-2 --input '{"prompt": "..."}' --save output.png

common apps:

• image: openai/gpt-image-2, reve/create, pruna/p-image
• upscale/edit: pruna/p-image-upscale, pruna/p-image-edit
• video: google/veo-2, seedance/seedance-2-i2v
• search: tavily/search, exa/search
• audio: elevenlabs/tts

knowledge — persistent agent memory

belt know search "query"                  # semantic search
belt know list --type observation         # list by type
belt know get namespace/name              # get details
belt know create ./file.md --type concept # create from file
echo "learned X" | belt know create - --name x --type observation  # from stdin
belt know delete <id>

types: skill, concept, observation, reference, preference

skills — reusable workflows

belt skill search "deployment"            # search registry
belt skill store --featured               # browse featured

# use on-demand (no install, stdout)
belt skill use namespace/skill-name       # from store
belt skill use github.com/user/repo       # from github
belt skill use user/repo --skill name     # pick from multi-skill repo

# install persistently
belt skill add namespace/skill-name       # auto-detects agents
belt skill add ns/name --agent claude-code
belt skill list                           # list installed

belt skill upload ./my-skill              # publish

connectors — mcp servers

belt mcp list                             # available connectors
belt mcp search "slack"                   # search
belt mcp connect slack                    # connect
belt mcp tools slack                      # list tools
belt mcp run slack send_message --input '{"channel": "#general", "text": "hello"}'

suggest — unified search

belt suggest "how to generate images"     # searches apps + skills + knowledge

tips

• use --json for structured output when piping
• use --save filename to save media outputs directly
• belt app sample generates valid input — start there for unfamiliar apps
• belt update to get latest version