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copilot-cli-custom-agents

Create and maintain GitHub Copilot CLI custom agents (.agent.md files). USE FOR: authoring .github/agents or ~/.copilot/agents profiles; frontmatter fields (description, target, name, model, tools, mcp-servers, disable-model-invocation, user-invocable, deferred-tool-loading, skills, reasoning-effort, sidekick); writing descriptions that drive auto-delegation (the CLI routes on description quality, like skills); building orchestrator + specialist squads with the task tool; /fleet parallel subagents; built-in agents (explore, task, research, code-review, rubber-duck, security-review, general-purpose); subagent depth/concurrency limits; list_agents and write_agent coordination. DO NOT USE FOR: VS Code-only fields beyond target (agents: allowlist, handoffs) or GitHub.com cloud agent configuration; MCP server authoring; SKILL.md authoring (use create-skill).

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NetFabric/NetFabric.Numerics星标 36(GitHub 36 + cccskills 0)
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包含的文件(6)

  • SKILL.md6.0 KB
  • references/authoring-workflow.md4.1 KB
  • references/delegation-and-squads.md7.2 KB
  • references/frontmatter-reference.md7.5 KB
  • references/undocumented-and-gotchas.md4.6 KB
  • references/writing-style.md3.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Copilot CLI Custom Agents

A custom agent is a Markdown file (.agent.md or .md) with YAML frontmatter plus a system-prompt body. The filename (minus extension) is the agent's ID. The CLI auto-delegates to it based on the description field — exactly like the skill/skill-invocation mechanism — so a vague description never gets invoked.

Anatomy

PartPurpose
Frontmatterdescription (required) + target: github-copilot (always set) + optional name, model, tools, mcp-servers, disable-model-invocation, user-invocable, deferred-tool-loading, skills, reasoning-effort, sidekick
BodySystem prompt: role, protocol, constraints. Max 30,000 characters
Location.github/agents/ or .claude/agents/ (project, walked to Git root, deepest wins) > ~/.copilot/agents/ (user) > <plugin>/agents/ (plugin, lowest priority)

Minimal example

---
description: Reviews code for OWASP Top 10 security issues. Use for security audits, "seccheck", or vulnerability review requests.
target: github-copilot
tools: ['read', 'search']
---

You are a security reviewer. Identify vulnerabilities following the OWASP Top 10
taxonomy. Report findings in a table with severity, location, and remediation.
Do NOT modify files.

Invocation

MethodSyntax
Auto-delegationMain agent matches your prompt against every agent's description
Inline mention@agent-name your prompt
Slash command/agent (browse/select), then enter a prompt
CLI flagcopilot --agent agent-name --prompt "..."
From another agenttask(agent_type="agent-name", prompt="...") — the CLI's subagent-dispatch tool

task takes exactly two parameters: agent_type (the target agent's ID) and prompt (the task to run). The subagent starts with a fresh, empty context — prompt is the only channel of information it receives, so the calling agent must write every fact the subagent needs (goal, constraints, file paths) directly into that string rather than assuming shared context. Details and examples → references/delegation-and-squads.md.

Built-in agents

explore, task, general-purpose, code-review, research (only via /research), rubber-duck, security-review — plus the undocumented configure-copilot agent for managing MCP servers/agents/skills. Full table → references/delegation-and-squads.md.

Workflow

  1. Scope one focused role per agent — read references/frontmatter-reference.md for every field
  2. Write a specific, keyword-dense description and a constraint-driven prompt body → references/writing-style.md — vague descriptions never get auto-invoked
  3. Restrict tools: to the minimum the role needs; strip edit from orchestrators and normally strip shell so they delegate. Retain narrowly scoped shell access only for an explicit orchestrator-owned dependency readiness preflight (for example, CBM installation/index verification), and forbid all other shell work in the prompt body
  4. Choose model: (and reasoning-effort:) using the model-selection skill before finalizing frontmatter — never leave it unset on the assumption an inherited default is adequate
  5. For multi-agent squads, adopt a naming prefix and use user-invocable: false on internal specialists → references/delegation-and-squads.md
  6. Always set target: github-copilot in the frontmatter — the CLI ignores it, but it's needed if the same file is ever opened in VS Code → references/frontmatter-reference.md
  7. Restart the CLI (or start a new session) to load new/edited agent files
  8. Check references/authoring-workflow.md if the agent doesn't load or isn't invoked
  9. Check references/undocumented-and-gotchas.md for fields/behaviors missing from the official reference table
  10. Run markdown-best-practices over the finished .agent.md — it's still a Markdown file (frontmatter fences, heading/list hygiene in the prompt body)

Reference Files

FileLoad When
references/frontmatter-reference.mdWriting or reviewing any frontmatter field, tool name/alias, or file location/priority rule
references/writing-style.mdWriting or reviewing a description or prompt body — trigger phrasing, constraints, output format
references/delegation-and-squads.mdBuilding an orchestrator, a specialist squad, using task/list_agents/write_agent, or /fleet
references/authoring-workflow.mdCreating an agent via the CLI wizard, testing it, or troubleshooting why it won't load/invoke
references/undocumented-and-gotchas.mdHitting a field or behavior the official CLI reference table omits; reconciling CLI vs. VS Code vs. cloud-agent differences

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中文简介正在准备中。当前显示原文说明。

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中文简介正在准备中。当前显示原文说明。

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中文简介正在准备中。当前显示原文说明。

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中文简介正在准备中。当前显示原文说明。

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