design-agent

name	design-agent
description	Design and create a new agent for the system. Captures requirements, selects model and tools, writes the system prompt, and configures memory scope. Use when the user says 'design an agent', 'create an agent', 'new agent for', or 'I need an agent that'.
argument-hint	[agent purpose and requirements]
context	fork
agent	system-architect

Design Agent: $ARGUMENTS

Existing agent patterns

!head -8 .claude/agents/*.md 2>/dev/null || echo "(Could not read existing agents)"

Agent standards (current)

Standards a new agent must meet — and the yardstick the system's own agents are held to. Build on plugin-dev:agent-development for general mechanics; this skill adds the vault layer.

• Frontmatter: name (lowercase-hyphens) · description · model · color (required) · tools (least-privilege) · plus the vault-local memory: extension.
• Description is the trigger. Form: "Use this agent when… Typical triggers include [2-4 prose scenarios]. See 'When to invoke' in the agent body." Cover proactive + reactive triggering and when NOT to use.
• "When to invoke" body section — 2-4 worked scenarios as prose bullets, including which skills fork into the agent (if any).
• model: inherit by default — let the agent ride the session model; hard-pin a tier only with a specific, justified need (not a reflexive opus/sonnet).
• Least-privilege tools — grant only what's needed (a read-only analysis agent gets Read, Grep, Glob, no Write/Edit). MCP tools (mcp__*, e.g. mcp__qmd__query) must be listed explicitly — a reference in the agent body or a forking skill does NOT grant access. Bash is a single grant covering all shell/CLI invocations (obsidian, defuddle, python).
• System prompt — second person; role → process → output format → edge cases; explain why; focused. memory: (user|project) is a vault-local extension backed by .claude/agent-memory/, not part of the upstream schema.

Your task

Design and create a new agent based on: $ARGUMENTS

Follow this workflow:

1. Capture requirements — From the description above, determine:

   • What is this agent's primary responsibility?
   • What tools does it need? (built-ins: Read, Grep, Glob, Write, Edit, Bash, WebSearch, WebFetch — plus any MCP tools like mcp__qmd__query, which must be granted explicitly)
   • Will it delegate to other agents or be delegated to?
   • Does it interact with external systems (Calendar, Reminders, web)?

2. Select model, color & memory — Choose:

   • Model: default inherit (ride the session model). Hard-pin a tier (opus/sonnet/haiku) only with a specific, justified need — and state why.
   • Color: a distinct UI color, required (blue/cyan analysis, green success, yellow validation, red critical, magenta generation).
   • Memory: user (transfers across projects) or project (codebase-specific) — vault-local extension backed by .claude/agent-memory/; omit if no persistent memory is needed.

3. Write frontmatter + system prompt:

   • description in the form "Use this agent when… Typical triggers include [2-4 prose scenarios]. See 'When to invoke' in the agent body." — cover proactive + reactive triggering and when NOT to use
   • A "## When to invoke" body section: 2-4 worked scenarios as prose bullets (note which skills fork into the agent, if any)
   • System prompt (second person): role → system context (vault name, file locations, git workflow) → process → quality standards → output format → edge cases → memory tracking. Explain why, not just what.

4. Create — Write the agent file to .claude/agents/{name}.md with valid frontmatter + system prompt

5. Verify — Check:

   • description carries triggers + a "When to invoke" pointer; a "## When to invoke" section exists (2-4 scenarios)
   • color present and valid; model is inherit (or a justified pin); tools is least-privilege
   • memory is user/project (or omitted); name is lowercase-with-hyphens

Output

Return:

• Agent created — Name, model, memory scope, tools
• Design decisions — Why this model, memory scope, and tool set
• Recommended skills — Which skills should fork to this agent
• Memory seeding — Suggestions for initial memory entries the agent should build