Open protocol for AI agent interoperability enabling standardized communication between agents, applications, and humans across different frameworks
SkillScore100Maintained
Automatic
◆AI Engineer pack
Last verified 8/18/2026
What it changes
Passed 23 of 23 test cases with the skill, and 7 of 23 without it.
Without skill30%
With skill100%
Checks it passed that the model alone missed
Yields incoming Message objects.
Yields an instance of AwaitInput.
Imports Client from acp_sdk.client.
and 23 more in the full report
16 fixed7 passed either way0 still failing0 broke
Pass-rate lift
+70 pp
Tokens
+301%
Agent turns
0%
Response time
-32%
Model gemini-3.6-flashMeasured 8/18/2026v123 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 16
Prompt
According to the Agent Communication Protocol specification, what four fields are required in an Agent Manifest?
What was checked, without and with the skill
Checked
Without skill
With skill
Specifies name, description, input_content_types, and output_content_types as required fields.
Missed
Passed
case-22 · gemini-3.6-flash · 8/18/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md1006 linessingle file
Agent Communication Protocol (ACP)
ACP is an open protocol for agent interoperability that solves the growing challenge of connecting AI agents, applications, and humans. It enables standardized communication across different frameworks and infrastructures.
Multi-Modal - Supports text, images, audio, video, and any MIME type
Async-First - Built primarily for asynchronous communication with sync support
Streaming - Real-time Server-Sent Events (SSE) for incremental updates
Stateful/Stateless - Sessions for maintaining state across interactions
Offline Discovery - Agents remain discoverable through embedded metadata
Framework Agnostic - Works with BeeAI, LangGraph, CrewAI, LlamaIndex, and more
Installation
# Create new project with uv
uv init --python '>=3.11' my_acp_project
cd my_acp_project
# Add ACP SDK
uv add acp-sdk
# Or with pip
pip install acp-sdk
Quick Start: Creating an Agent
Basic Echo Agent
import asyncio
from collections.abc import AsyncGenerator
from acp_sdk.models import Message
from acp_sdk.server import Context, RunYield, RunYieldResume, Server
server = Server()
Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.