multi-tool-batch-invocation

Multi-Tool Parallel Batch Invocation Protocol

Overview

When an agent needs to inspect 4 related files (e.g., schema.prisma, auth.ts, routes.ts, and types.ts), naive agents execute 4 sequential back-and-forth turns:

• Turn 1: Call view_file("schema.prisma") $\rightarrow$ Wait for response
• Turn 2: Call view_file("auth.ts") $\rightarrow$ Wait for response
• Turn 3: Call view_file("routes.ts") $\rightarrow$ Wait for response
• Turn 4: Call view_file("types.ts") $\rightarrow$ Wait for response

Sequential tool calling re-sends the entire conversation transcript 4 separate times, incurring 4 API roundtrips and 15 to 20 seconds of latency.

The Multi-Tool Batch Invocation Protocol leverages modern function calling specifications to emit multiple tool calls in a single turn (tool_calls: [...]), executing independent operations concurrently via asyncio.gather or Promise.all.

Sequential Single-Tool Turns vs. Parallel Batch Tooling

┌─────────────────────────────────────────────────────────────┐
│                 Tool Execution Roundtrips                   │
│                                                             │
│  Sequential Tool Calls (4 Turns / 14,800 Tokens):           │
│  • Turn 1: Reads `schema.prisma` ──► 1 API Roundtrip (3.2s) │
│  • Turn 2: Reads `auth.ts`       ──► 1 API Roundtrip (3.4s) │
│  • Turn 3: Reads `routes.ts`     ──► 1 API Roundtrip (3.5s) │
│  • Turn 4: Reads `types.ts`      ──► 1 API Roundtrip (3.1s) │
│  ↳ 4 Roundtrips, 13.2s total latency, 14,800 tokens billed  │
│                                                             │
│  Parallel Batch Invocation (1 Turn / 4,200 Tokens):         │
│  • Turn 1: Model emits array of 4 `view_file` tool calls    │
│    ↳ Client executes all 4 reads concurrently (0.05s CPU)   │
│  • Turn 2: Model receives all 4 results in 1 batch return   │
│  ↳ 1 Roundtrip, 3.4s total latency (3.8x Faster, 71% Cut!)  │
└─────────────────────────────────────────────────────────────┘