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Set an ibl.ai agent's LLM provider and model via the platform API — list available provider/model cards and write the selection through the agent settings endpoint. Use when changing which model an agent runs on.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
| name | iblai-api-agent-llm |
| description | Set an ibl.ai agent's LLM provider and model via the platform API — list available provider/model cards and write the selection through the agent settings endpoint. Use when changing which model an agent runs on. |
Set an agent's LLM provider and model: list the available provider/model cards
and write the chosen provider + model through the same settings/ endpoint that
backs the rest of the agent configuration. Use when changing which model an agent
runs on.
https://api.iblai.appAuthorization: Api-Token $IBLAI_API_KEY on every request.{org} = $IBLAI_ORG, {username} = $IBLAI_USERNAME,
{mentor} = the agent's unique id (e.g. d17dc729-60fd-4363-81a0-f67d9318b03e).settings/ endpoint —
PUT …/users/{username}/mentors/{mentor}/settings/./iblai-api-login first to populate IBLAI_ORG,
IBLAI_USERNAME, and IBLAI_API_KEY.https://api.iblai.app/dm/api/ai-mentor/orgs/{org}/users/{username}/mentors/{mentor}/settings/ — current provider/model.https://api.iblai.app/dm/api/ai-mentor/orgs/{org}/users/{username}/mentor-llms/?mentor_id={mentor} — provider/model cards.…/users/{username}/mentors/{mentor}/settings/ — set provider/model:
{
"llm_provider": "string (required)",
"llm_name": "string (required)"
}
Switch an agent to OpenAI's GPT-4o:
curl -X PUT \
"https://api.iblai.app/dm/api/ai-mentor/orgs/$IBLAI_ORG/users/$IBLAI_USERNAME/mentors/$MENTOR/settings/" \
-H "Authorization: Api-Token $IBLAI_API_KEY" \
-F "llm_provider=openai" \
-F "llm_name=gpt-4o"
llm_provider +
llm_name pair that appears in that list — values must match a real card.settings/ endpoint, so it sits
alongside the other configuration fields on the same agent.Configure an ibl.ai agent's embed/widget settings via the platform API — anonymous access, custom CSS/JS, mode, voice/attachment toggles, starter prompts, SSO, share links, and redirect tokens. Use when embedding an agent on an external website.
Measure and improve agent quality via the platform API — evaluation datasets, dataset items (JSON, CSV upload, or from chat traces), experiment runs, LLM-as-Judge and human-annotation scoring, score configs, and CSV export. Use to test an agent against a dataset and grade the results.
MCP connectors for ibl.ai agents, end to end — register MCP servers (featured multi-tenant sharing, enable/disable, OAuth service linkage), manage credential connections with the auth_type × scope matrix (org / agent / per-user), wire servers onto an agent, run the OAuth connected-service lifecycle, handle per-user in-chat OAuth (the oauth_required / oauth_connection_resolved chat events), and debug MCP auth failures (401s, missing OAuth prompts, agents ignoring servers). Use when wiring an agent to external MCP servers and tools, or designing/troubleshooting MCP auth.
Manage an ibl.ai agent's memories via the platform API — list and filter agent (mentor) memories (by category, user, email, date), curate global (cross-agent) memories, add/edit/delete memories, manage memory categories, and toggle capture/recall settings. Use when inspecting or curating what an agent remembers.
Connect/disconnect an ibl.ai agent's sandbox (Claw) instance, manage Claw instances, push config, run health/connectivity checks, and set the agent's model — via the platform API. Use when wiring an agent to a sandboxed workspace.
Manage an ibl.ai organization's CRM via the platform API — people, organizations, pipelines and stages, lead sources, deals (with stage-move/won/lost actions), activities, and tags. Org-wide sales/relationship management. Use for lead capture, pipelines, and deal flow.