team-leader

Team Leader

Decomposes a scenario into parallel sub-problems and spawns one general-purpose (or Explore) agent per sub-problem directly via the Agent tool. team-leader is not a valid subagent_type — it is a decomposition pattern, not an agent type. Never pass subagent_type: "team-leader" to the Agent tool; it will fail with "Agent type 'team-leader' not found."

Pattern

Decompose — identify 2–6 bounded sub-problems with no overlap
Spawn in parallel — call the Agent tool N times simultaneously, once per sub-problem, each with subagent_type: "general-purpose" (or "Explore" for pure research tasks)
Synthesize — integrate findings into a coherent unified output

When to use

Problem has multiple independent angles (e.g., security + performance + API design)
Different parts of a problem require different agent types (exploration vs. coding)
Parallel execution would meaningfully reduce total time
You'd otherwise context-switch between unrelated concerns mid-task

When NOT to use

Sub-problems are sequential and each depends on the previous result
The problem is simple enough for a single agent
Discovery must precede decomposition (run explore first, then team-leader)

Same-File Edit Constraint

When all sub-problems require editing the same file, parallel agents will clobber each other — the second agent's old_string may no longer exist after the first agent modified it. Do NOT spawn parallel write agents in this case.

Pattern to use instead:

Decompose into read-only research agents (spawn in parallel using subagent_type: "Explore") — each agent identifies the exact old_string → new_string patch for its sub-problem. Research agents read the file but make no edits.
Collect all patches from the agent results.
Apply all patches sequentially in a single pass — either directly with the Edit tool or via one agent briefed with all patches.

Example decomposition for "fix 6 prose issues in the same QMD":

Agent A (Explore): find exact text for issues 1, 2, 3 — return verbatim old/new strings
Agent B (Explore): find exact text for issues 4, 5, 6 — return verbatim old/new strings
[collect results]
Apply all 6 Edit calls sequentially

How to detect this situation before spawning: Before issuing the Agent tool calls, check: do any two sub-problems write to the same file? If yes, switch to the research-first pattern.

Invocation

@team-leader <scenario description>

Claude (the primary agent) performs the decomposition itself, then spawns parallel agents via the Agent tool:

Agent tool call 1: subagent_type="general-purpose", prompt="<sub-problem A briefing>"
Agent tool call 2: subagent_type="general-purpose", prompt="<sub-problem B briefing>"
Agent tool call 3: subagent_type="Explore",         prompt="<sub-problem C briefing>"

All three calls are issued in the same turn so they execute in parallel. Collect results, then synthesize.

Example decompositions

"Review the checkout flow for problems" →

Sub-problem A: frontend UX and accessibility issues
Sub-problem B: API contract and error handling
Sub-problem C: payment integration edge cases

"Design a rate limiting system" →

Sub-problem A: algorithm options and trade-offs
Sub-problem B: data store and persistence requirements
Sub-problem C: API surface and client impact