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skills/core/external_agents.md

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+---
+name: external_agents
+description: "External agent capability profiles and delegation guidance"
+domain:
+  - general
+  - coding
+  - frontend
+  - backend
+  - devops
+  - writing
+  - documentation
+  - automation
+always_on: true
+trigger: "When deciding whether to use the native agent or an external CLI agent"
+---
+
+# External Agent Selection Skill
+
+## Goal
+Choose between the OPC native agent and available external agents based on the actual task,
+the configured agent profile, and expected execution style. Do not rely on fixed domain
+rules alone.
+
+## Native Agent
+- Strong default choice for lightweight reasoning, conversation, clarification, and tasks
+  that benefit from tight integration with OPC memory, organization, and tool orchestration.
+- Prefer native when direct continuity inside OPC matters more than delegating to an
+  external CLI agent.
+
+## External CLI Agents
+- External agents such as Cursor, Claude Code, and Codex are usually strongest for complex,
+  tool-heavy, multi-step execution where a dedicated CLI agent can work in an isolated
+  workspace.
+- Their strengths are not limited to writing code. They can also handle bash-driven tasks
+  such as generating or transforming Markdown, documents, PDFs, slide content, reports,
+  scripts, and repository-wide edits.
+- When choosing among external agents, consider the configured model, whether the run should
+  start a new session or continue an existing one, and any extra CLI arguments already set.
+
+## Decision Heuristics
+- Prefer an external agent when the task requires sustained autonomous execution over files,
+  shell commands, or project artifacts.
+- Prefer an external agent when the request is complex enough that a specialized coding or
+  CLI workflow is likely to outperform the native agent.
+- Prefer native when the task is simple, mostly conversational, or better served by keeping
+  reasoning and tool use inside OPC itself.
+- If multiple external agents are available, pick the one whose configured profile best
+  matches the task instead of following a fixed ranking.
+
+## Approval And Autonomy
+- Treat external agents as part of the same bounded-autonomy system as native tools.
+- Routine, low-risk actions can be auto-approved when they match learned user preferences.
+- Ambiguous, sensitive, or destructive operations should trigger escalation to the user.
+- Learn from explicit user approvals or rejections so future runs behave more like the
+  user's trusted second self rather than a static automation pipeline.