Stop guessing which skills work.

1from agents import Agent, Runner
2from decimalai.openai_agents import agent_config
3
4# support-agent's skills include refund-replies
5support = agent_config(
6    "support-agent", fallback="You help customers."
7)
8
9agent = Agent(
10    name=support.name,
11    instructions=support.instructions,
12    tools=[*support.tools],
13)
14
15question = "How much do I get back on my opened $49.00 kettle?"
16print(Runner.run_sync(agent, question).final_output)

 from agents import Agent, Runner
+from decimalai.openai_agents import agent_config
 
+support = agent_config(
+    "support-agent", fallback="You help customers."
+)
 
 agent = Agent(
     name="support-agent",
-    instructions="You help customers.",
+    instructions=support.instructions,
+    tools=[*support.tools],
 )

1from langchain.agents import create_agent
2from decimalai.langchain import agent_config
3
4# support-agent's skills include refund-replies
5support = agent_config(
6    "support-agent", fallback="You help customers."
7)
8
9agent = create_agent(
10    "openai:gpt-5.4-mini",
11    tools=[],
12    middleware=[support.middleware],
13)
14
15question = "How much do I get back on my opened $49.00 kettle?"
16message = {"role": "user", "content": question}
17result = agent.invoke({"messages": [message]})
18print(result["messages"][-1].text)

 from langchain.agents import create_agent
+from decimalai.langchain import agent_config
 
+support = agent_config(
+    "support-agent", fallback="You help customers."
+)
 
 agent = create_agent(
     "openai:gpt-5.4-mini",
     tools=[],
-    system_prompt="You help customers.",
+    middleware=[support.middleware],
 )

1import asyncio
2from claude_agent_sdk import ClaudeAgentOptions, ResultMessage
3from decimalai.claude_agent_sdk import agent_config
4
5# support-agent's skills include refund-replies
6support = agent_config(
7    "support-agent", fallback="You help customers."
8)
9options = ClaudeAgentOptions(
10    model="claude-haiku-5-5",
11    tools=[],            # none of Claude Code's own tools
12    setting_sources=[],  # nothing from this machine's settings
13)
14question = "How much do I get back on my opened $49.00 kettle?"
15
16async def main():
17    async with support.run(question) as run:
18        async for message in run.query(options=options):
19            if isinstance(message, ResultMessage):
20                print(message.result)
21
22asyncio.run(main())

 from claude_agent_sdk import ClaudeAgentOptions, query
+from decimalai.claude_agent_sdk import agent_config
 
+support = agent_config(
+    "support-agent", fallback="You help customers."
+)
 options = ClaudeAgentOptions(
     model="claude-haiku-5-5",
+    tools=[],
+    setting_sources=[],
 )
 
 async def main():
-    async for message in query(prompt=question, options=options):
-        print(message)
+    async with support.run(question) as run:
+        async for message in run.query(options=options):
+            print(message)

1import decimalai.crewai
2from crewai import LLM, Agent, Crew, Task
3
4agent = Agent(
5    role="Support agent",
6    goal="Answer the customer",
7    backstory="You help customers.",
8    llm=LLM(model="gpt-5.4-mini"),
9    skills=decimalai.crewai.skills(),  # includes refund-replies
10    tools=decimalai.crewai.skill_tools(),
11)
12
13question = "How much do I get back on my opened $49.00 kettle?"
14task = Task(
15    description=question,
16    expected_output="The refund amount and the reason",
17    agent=agent,
18)
19print(Crew(agents=[agent], tasks=[task]).kickoff())

+import decimalai.crewai
 from crewai import LLM, Agent
 
 agent = Agent(
     role="Support agent",
     goal="Answer the customer",
     backstory="You help customers.",
     llm=LLM(model="gpt-5.4-mini"),
+    skills=decimalai.crewai.skills(),
+    tools=decimalai.crewai.skill_tools(),
 )

1from pydantic_ai import Agent
2from decimalai.pydantic_ai import agent_config
3
4# support-agent's skills include refund-replies
5support = agent_config(
6    "support-agent", fallback="You help customers."
7)
8
9agent = Agent(
10    "openai:gpt-5.4-mini",
11    name=support.name,
12    capabilities=[support],
13)
14
15question = "How much do I get back on my opened $49.00 kettle?"
16print(agent.run_sync(question).output)

 from pydantic_ai import Agent
+from decimalai.pydantic_ai import agent_config
 
+support = agent_config(
+    "support-agent", fallback="You help customers."
+)
 
 agent = Agent(
     "openai:gpt-5.4-mini",
-    instructions="You help customers.",
+    name=support.name,
+    capabilities=[support],
 )

1import asyncio
2from google.adk.agents import LlmAgent
3from google.adk.runners import InMemoryRunner
4from decimalai.adk import agent_config
5
6# support-agent's skills include refund-replies
7support = agent_config(
8    "support-agent", fallback="You help customers."
9)
10
11agent = LlmAgent(
12    name="support_agent",
13    model="gemini-3.5-flash",
14    instruction=support.instruction,
15    tools=[*support.tools],
16)
17
18runner = InMemoryRunner(agent=agent)
19question = "How much do I get back on my opened $49.00 kettle?"
20asyncio.run(runner.run_debug(question))

 from google.adk.agents import LlmAgent
+from decimalai.adk import agent_config
 
+support = agent_config(
+    "support-agent", fallback="You help customers."
+)
 
 agent = LlmAgent(
     name="support_agent",
     model="gemini-3.5-flash",
-    instruction="You help customers.",
+    instruction=support.instruction,
+    tools=[*support.tools],
 )