Agent Skills › Companion-Inc/feynman › using-model-endpoint

using-model-endpoint

GitHub

该技能用于调用已配置的模型端点并解释其响应，涵盖远程API、本地服务或自定义连接器。流程包括确认端点状态、构建请求、保存元数据、验证响应及区分预测与事实，适用于需要模型推理的任务场景。

skills/using-model-endpoint/SKILL.md Companion-Inc/feynman

Trigger Scenarios

需要调用已注册的模型端点进行推理处理远程模型API或本地模型服务的请求使用自定义连接器支持的预测器

Install

npx skills add Companion-Inc/feynman --skill using-model-endpoint -g -y

More Options

Use without installing

npx skills use Companion-Inc/feynman@using-model-endpoint

指定 Agent (Claude Code)

npx skills add Companion-Inc/feynman --skill using-model-endpoint -a claude-code -g -y

安装 repo 全部 skill

npx skills add Companion-Inc/feynman --all -g -y

预览 repo 内 skill

npx skills add Companion-Inc/feynman --list

SKILL.md

Frontmatter

{
    "name": "using-model-endpoint",
    "description": "Call a configured Feynman model endpoint and interpret its response. Use when a task needs inference from a registered endpoint, remote model API, local model service, or custom connector-backed predictor."
}

Using Model Endpoint

Use this skill after a model endpoint is already configured or explicitly chosen.

Workflow:

Confirm endpoint identity, auth status, input schema, output schema, model version, and rate/size limits.
Build a minimal request with explicit inputs and no hidden context.
Save request metadata, response, latency, status, and parsing code as artifacts without exposing secrets.
Validate response shape and handle model errors as evidence, not as missing work to hide.
Interpret predictions separately from source-backed facts.

When the endpoint is not configured, switch to managed-model-endpoints or compute-env-setup instead of pretending inference ran.