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-use-builtin-toolsgit 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-use-builtin-tools)<a href="https://agentmods.dev/skills/ag2ai/ag2-skills/ag2-use-builtin-tools"><img src="https://agentmods.dev/badge/skills/ag2ai/ag2-skills/ag2-use-builtin-tools/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-use-builtin-tools"><img src="https://agentmods.dev/badge/skills/ag2ai/ag2-skills/ag2-use-builtin-tools.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 | $0.00103 | $0.01410 |
| Opus 5 | $0.00051 | $0.00705 |
| Sonnet 5 | $0.00021 | $0.00282 |
| Haiku 4.5 | $0.00010 | $0.00141 |
Grade A, and why
ag2-use-builtin-tools 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 11d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use AG2's built-in tools
When to use
Reach for this skill when the user wants to add a capability that AG2 already ships. Two families:
- Provider-native tools (
ag2.tools—WebSearchTool,CodeExecutionTool, etc.) — executed server-side by Anthropic / OpenAI / Gemini. No Python implementation on your side. - Common toolkits (
ag2.tools—FilesystemToolkit,DuckDuckSearchTool,TavilySearchTool,SkillsToolkit; plusExaToolkitfromag2.extensions.tools.search) — regular Python that runs in your process and works with every provider.
For shell commands, use ag2-shell-tool (it's important enough to live in its own skill).
For custom Python tools, use ag2-add-custom-tool.
60-second recipes
Web search (provider-native)
from ag2 import Agent
from ag2.config import AnthropicConfig
from ag2.tools import WebSearchTool, UserLocation
agent = Agent(
"researcher",
config=AnthropicConfig(model="claude-sonnet-4-6"),
tools=[
WebSearchTool(
max_uses=5,
user_location=UserLocation(country="US"),
allowed_domains=["github.com", "pypi.org"],
blocked_domains=["pinterest.com"],
),
],
)
Web fetch (Anthropic / Gemini only)
from ag2.tools import WebFetchTool
tools = [WebFetchTool(max_uses=3, max_content_tokens=50000, citations=True)]
Code execution
from ag2.tools import CodeExecutionTool
agent = Agent("analyst", config=config, tools=[CodeExecutionTool()])
MCP server integration
from ag2.tools import MCPServerTool
tools = [
MCPServerTool(
server_url="https://mcp.example.com/sse",
server_label="my-tools",
allowed_tools=["search", "summarize"],
),
]
Image generation (OpenAI Responses only)
from ag2.config import OpenAIResponsesConfig
from ag2.tools import ImageGenerationTool
agent = Agent(
"designer",
config=OpenAIResponsesConfig(model="gpt-4.1"),
tools=[ImageGenerationTool(quality="high", size="1024x1024", output_format="png")],
)
reply = await agent.ask("Generate a logo for a coffee shop.")
images = reply.files # list[BinaryResult]
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 146 lines · 103 tokens per session scan A 606f5d6b29fe
ag2-use-builtin-tools is a skill published in the GitHub repository ag2ai/ag2-skills (10 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 103 tokens to every session and 1,410 once invoked, about $0.0005 per session on Opus 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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