Agent Skills
› companion-inc/feynman
› using-model-endpoint
using-model-endpoint
GitHub调用已配置模型端点并解读响应,适用于推理任务。流程包括确认端点状态、构建请求、保存元数据与响应、验证形状及处理错误,并将预测结果与事实分离。
Trigger Scenarios
需要调用远程或本地模型进行推理
使用自定义连接器预测器
Install
npx skills add companion-inc/feynman --skill using-model-endpoint -g -y
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.
Version History
- 54d08a3 Current 2026-07-25 07:16


