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belt

Use the belt CLI — run 250+ AI apps, manage knowledge, search skills, connect MCP servers. Purpose-built CLI interface for agent workflows — typed inputs, schema validation, no raw API calls needed.

DeepseekModel 官方收录技能 质量 良好 · 64 v1.0.0

获取

https://deepseekmodel.com/api/download.php?id=belt-sh-cli-agents-skills-belt-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name belt description Use the belt CLI — run 250+ AI apps, manage knowledge, search skills, connect MCP servers. Purpose-built CLI interface for agent workflows — typed inputs, schema validation, no raw API calls needed. allowed-tools Bash(belt *), Bash(which belt), Bash(brew install inference-sh/tap/belt), Bash(scoop install belt), Bash(npm install -g @inferencesh/belt) belt cli belt is the cloud platform cli for ai agents. single ~4mb binary, no runtime dependencies. using a purpose-built cli means your agent operates through a constrained, typed interface instead of writing raw curl commands or sdk calls. every operation goes through schema validation — fewer tokens, fewer errors, and no credential leakage. install first check if belt is already installed: which belt && belt --version if already installed, skip to authenticate. package managers (recommended — verified through each registry's trust chain): brew install inference-sh/tap/belt # macos / linux (homebrew tap, signed) scoop bucket add belt https://github.com/belt-sh/scoop-belt && scoop install belt # windows npm install -g @inferencesh/belt # node.js (global install, pinned in package.json) manual install (full control — download, verify, then run): curl -fsSL https://cli.inference.sh -o /tmp/belt-install.sh the installer is a short, readable shell script. it detects your os and architecture, downloads the matching binary from dist.inference.sh , verifies the binary's sha-256 checksum against the published manifest, and places it in your path. no elevated permissions required. the installer source is publicly readable — review it before running: cat /tmp/belt-install.sh # review the script sh /tmp/belt-install.sh # run after review authenticate belt login belt me set up agent integration belt plugin init claude # claude code belt plugin init codex # openai codex belt plugin init cursor # cursor quick start belt suggest "what tool should i use" # unified search across apps, skills, knowledge belt app store # browse ai apps belt app store --category video # filter by category belt app get <namespace/name> # see schema, pricing, functions belt app sample <namespace/name> # generate sample input json belt app run <namespace/name> --input input.json # run an app belt balance # check credits common workflows image and video generation: belt app get bytedance/seedance-2-0 # check schema — file fields accept local paths belt app sample bytedance/seedance-2-0 --save input.json # edit input.json, then: belt app run bytedance/seedance-2-0 --input input.json file fields (type: file in schema) accept local paths directly — the cli auto-uploads them: belt app run bytedance/seedance-2-0 --input '{"image": "./photo.jpg", "prompt": "make it cinematic"}' check pricing before running: belt app pricing <namespace/name> # see cost formula belt app pricing <namespace/name> --json # machine-readable multi-function apps (e.g. apps with list_voices, list_resources, etc.): belt app get heygen/avatar-video # shows all functions with schemas belt app sample heygen/avatar-video -f list_resources # sample for a specific function belt app run heygen/avatar-video -f list_resources --input '{}' knowledge and skills: belt knowledge list --json # your knowledge entries belt knowledge search "react patterns" # semantic search belt skill list # your skills belt skill store search "video" # find skills in the store belt skill use <namespace/name> # load a skill on-demand mcp connectors: belt mcp list # browse available connectors belt mcp connect slack # connect one belt mcp run slack send_message --input '{"channel": "#general", "text": "hello"}' machine-readable output: all list commands support --json for structured output: belt app list --json belt app store --json belt task list --json belt knowledge list --json belt skill list --json belt mcp list --json belt secrets list --json belt me --json belt balance --json tips belt app sample generates ready-to-edit input json from the app schema file fields show ./your-file.jpg in samples — just replace with your actual file path belt suggest searches apps, skills, and knowledge in one call belt task cost <task-id> shows actual cost after a run belt app run --no-wait submits without blocking, belt task get <id> to check later use --session new for stateful apps that keep gpu warm between calls disable hooks for a project # .beltsh/config.json { "hooks_disabled" : true } or set BELT_NO_HOOKS=1 in your environment. links belt.sh · docs · trust · source
Agent 识别该技能的关键词,点击任意一个即可复制。

该技能未提供触发词。

下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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