Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ag2ai/ag2-skills --skill ag2-testinggit clone --depth 1 https://github.com/ag2ai/ag2-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ag2ai/ag2-skills/ag2-testing)<a href="https://agentmods.dev/skills/ag2ai/ag2-skills/ag2-testing"><img src="https://agentmods.dev/badge/skills/ag2ai/ag2-skills/ag2-testing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ag2ai/ag2-skills/ag2-testing"><img src="https://agentmods.dev/badge/skills/ag2ai/ag2-skills/ag2-testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.01567 |
| Opus 5.5 | $0.00032 | $0.00627 |
| Sonnet 5.5 | $0.00016 | $0.00313 |
| Haiku 4.5 | $0.00008 | $0.00157 |
Grade A, and why
ag2-testing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing agents and tools
When to use
Writing tests for code that builds AG2 Agents, custom @tool functions, middleware, or response schemas — anywhere you don't want to make real LLM API calls.
60-second recipe — mock an LLM response
import pytest
from ag2 import Agent
from ag2.testing import TestConfig
@pytest.mark.asyncio
async def test_mocked_response():
agent = Agent("test_agent")
reply = await agent.ask("Hi!", config=TestConfig("This is a mocked response."))
assert reply.body == "This is a mocked response."
TestConfig(*responses) replaces the model client. Each positional arg is the mocked response for the next LLM call within an ask() — strings for text replies, ToolCallEvent for tool dispatches. (The cursor is per-ask(); see "Multi-turn mock" below for what that means across multiple turns.)
Simulate a successful tool call
Pass a ToolCallEvent first (the model "decides" to call the tool), then the final answer:
import pytest
from ag2 import Agent
from ag2.events import ToolCallEvent
from ag2.testing import TestConfig
@pytest.mark.asyncio
async def test_tool_success():
def my_tool() -> str:
return "tool execution result"
agent = Agent("test_agent", tools=[my_tool])
config = TestConfig(
ToolCallEvent(name="my_tool"),
"final result",
)
reply = await agent.ask("Please use my_tool", config=config)
assert reply.body == "final result"
Test tool error paths
If a tool raises, the exception propagates to ask():
@pytest.mark.asyncio
async def test_tool_raises():
def failing_tool() -> str:
raise ValueError("Something went wrong")
config = TestConfig(
ToolCallEvent(name="failing_tool"),
"result",
)
agent = Agent("test_agent", config=config, tools=[failing_tool])
with pytest.raises(ValueError, match="Something went wrong"):
await agent.ask("Hi!")
Tool not found
If the LLM calls a tool the agent doesn't have, the framework raises ToolNotFoundError:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 149 lines · 80 tokens per session scan A eaa62b032972
ag2-testing is a skill published in the GitHub repository ag2ai/ag2-skills (12 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 1,567 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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