القائمة
Real-time web search via Azure AI Foundry Responses API with bing_grounding tool. Get current information with citations — no egress policy needed.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Pair with a kars cluster and offload heavy tasks to governed cloud sandboxes with GPU / foundation-model inference / Azure AI services, or communicate with other agents over end-to-end encrypted AgentMesh. Triggers on natural-language intents like "offload to the cloud", "run this on Azure", "ask my cluster to…", "send a message to agent X", "who is on the mesh", "check my inbox", "is my offload done".
Behavioral governance for OpenClaw agents via AGT — tool-level policy, inter-agent trust, audit logging.
Spawn secure isolated sub-agent sandboxes, delegate tasks via AGT mesh, receive results, and destroy sub-agents. Uses the kars_spawn, kars_mesh_send, kars_mesh_inbox, and kars_spawn_destroy tools.
Query and inspect Foundry prompt agents and invoke Foundry tools via the Responses API. OpenClaw is the orchestrator — Foundry provides managed AI services.
Python code execution via Azure AI Foundry Responses API with code_interpreter tool. Data analysis, charts, and math in a managed sandbox.
Manage persistent conversations via Foundry Conversations API. Create conversations, add messages, and maintain history across sessions.
| name | foundry-web-search |
| description | Real-time web search via Azure AI Foundry Responses API with bing_grounding tool. Get current information with citations — no egress policy needed. |
| metadata | {"openclaw":{"requires":{"env":["FOUNDRY_PROJECT_ENDPOINT"]},"primaryEnv":"FOUNDRY_PROJECT_ENDPOINT"}} |
You have access to real-time web search via the Foundry Responses API bing_grounding tool. Results come with inline URL citations. No sandbox egress policy exceptions needed — search runs server-side.
Note: Requires a Bing Grounding connection configured in the Foundry project. If not available, the model will answer from its training data instead.
All requests: http://localhost:8443 with ?api-version=2025-11-15-preview. Auth is automatic.
curl -s -X POST 'http://localhost:8443/openai/responses?api-version=2025-11-15-preview' \
-H 'Content-Type: application/json' \
-d '{"model":"gpt-4.1","input":"What are the latest Azure AI Foundry announcements?","tools":[{"type":"bing_grounding","bing_grounding":{"search_configurations":[{"project_connection_id":"AUTO_DISCOVERED_AT_RUNTIME"}]}}],"store":false}'
The response includes the answer with inline URL citations.
If Bing is not configured, use plain chat — the model answers from training data:
curl -s -X POST 'http://localhost:8443/v1/chat/completions' \
-H 'Content-Type: application/json' \
-d '{"model":"gpt-4.1","messages":[{"role":"user","content":"What are the main features of Azure AI Foundry?"}]}'