xuzhougeng/using-model-endpoint
Invoke an already configured model endpoint from a supported Wisp execution context and capture the bounded inference as a Run. Use only when the endpoint URL and authentication are already available inside that context; this skill does not register or manage services.
npx skills add https://github.com/xuzhougeng/wisp-science --skill using-model-endpoint
Wisp can record a bounded client invocation as a Run, but it does not register
or manage the endpoint. Require all of the following:
local, wsl:<distro>, or ssh:<alias> context;or the endpoint client's own external configuration;
Do not ask the user to paste secrets into the command, project files, or chat.
Wisp exposes no credential accessor to the Agent and does not inject keyring
values into run_in_context commands.
runs/call_endpoint.py. Read theURL and credential variable names at runtime; never embed secret values.
input_paths. Keep largeinputs at an existing absolute remote path.
run_in_context and register the response withoutput_specs:
{
"context_id": "ssh:gpu-box",
"title": "Existing endpoint inference",
"command": "source ~/miniforge3/etc/profile.d/conda.sh && conda activate endpoint-client && python call_endpoint.py --input request.json --output /home/me/wisp-results/endpoint/response.json",
"timeout_secs": 300,
"input_paths": ["runs/call_endpoint.py", "data/request.json"],
"output_specs": [
{
"glob": "ssh://gpu-box/home/me/wisp-results/endpoint/response.json",
"kind": "json",
"residency": "remote"
}
]
}
monitor_run once when waitingis useful, get_run once for a snapshot, or cancel_run to stop.
Local and WSL Runs are capped at 300 seconds and do not accept input_paths.
Keep their client and outputs in host-visible project paths. If endpoint setup,
tunnelling, health management, or deployment is required, stop and load
managed-model-endpoints for the explicit current boundary.
Take xuzhougeng/using-model-endpoint from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.