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agent-core

AgentScope agent, toolkit, permission, event, and local skill-loading workflows.

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VectorSpaceLab/AREX-Skill
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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
agent-core
description
AgentScope agent, toolkit, permission, event, and local skill-loading workflows.
disable-model-invocation
true
metadata
{"disco-role":"operating"}
license
Apache 2.0
# agent-core Use this sub-skill for the day-to-day AgentScope SDK surface: agents, toolkits, built-in tools, task tools, permissions, message and event streams, and local skills. ## Read first - `references/api-reference.md` for the verified constructors, exported classes, and key defaults. - `references/workflows.md` for end-to-end agent setup patterns. - `references/troubleshooting.md` for import, permission, tool, and skill-loading failures. ## Typical triggers - Build an `Agent` with a `Toolkit` and a model. - Add or debug built-in tools like Bash, Read, Write, Edit, Glob, Grep, or PowerShell. - Use task tools, MCP tools, or function-wrapped tools. - Load local skills with `LocalSkillLoader` and inspect skill instructions. - Handle `reply_stream` events, interruption, or structured output. ## What belongs here - `Agent`, `ContextConfig`, `InjectionConfig`, `ModelConfig`, `ReActConfig` - `Toolkit`, `ToolGroup`, `FunctionTool`, `MCPTool`, `ToolBase` - `Msg`, `UserMsg`, `AssistantMsg`, `SystemMsg`, event classes, permission types, state types - `Skill`, `SkillLoaderBase`, `LocalSkillLoader` - task tools and built-in shell/file/search helpers ## What does not belong here - Provider selection, credentials, or model-family specifics → `provider-connectors` - RAG, vector stores, or memory backends → `rag-memory` - Service deployment and backend wiring → `service-platform` - Workspace/sandbox backend setup → `workspace-sandboxes` ## Use pattern 1. Start with the `Agent` and the smallest `Toolkit` that covers the task. 2. Add permission or injection config only when the workflow needs it. 3. Read `reply_stream` events when you need tool-call or interruption detail. 4. Use `LocalSkillLoader` and `Toolkit(skills_or_loaders=...)` when the task depends on reusable skills. 5. Escalate to the other sub-skills only when the problem is actually provider-, retrieval-, service-, or workspace-specific. ## Shared diagnostics - Run `../../scripts/check_env.py` first if imports or exports look stale. - Read `references/troubleshooting.md` before editing if the failure looks like a config or permission issue. ## Cross-links - If the model itself is the problem, switch to `provider-connectors`. - If the task uses a sandboxed workspace backend, switch to `workspace-sandboxes`. - If the task is about retrieval or memory, switch to `rag-memory`.
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