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開発・技術 · SKILL.md

agent-core

agent-core

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

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

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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