Predefined Tools

Ready-to-use tools provided by Connic. Import these directly into your agents without writing any code.

Predefined tools are built-in capabilities that Connic provides out of the box. Unlike custom tools where you write Python functions, predefined tools are ready to use. Just add their name to your agent's tools list.

• No Code Required: Just add the tool name to your YAML config. Implementation is handled by Connic.
• Secure by Default: Tools run in isolated environments with proper authentication and access controls.
• Environment Scoped: Data is isolated per environment. Dev and prod never mix.

version: "1.0"

name: assistant
model: gemini/gemini-2.5-pro
description: "An assistant with knowledge and orchestration capabilities"
system_prompt: |
  You have access to a persistent knowledge base.
  Search it before answering questions.

tools:
  - query_knowledge   # Predefined tool - no code needed
  - store_knowledge
  - trigger_agent

You can also import and call predefined tools directly from your custom Python tools. This lets you build complex orchestration logic that combines knowledge queries with agent triggers.

from connic.tools import trigger_agent, query_knowledge

async def research_and_summarize(topic: str) -> dict:
    """Research a topic and return a summary.
    
    Args:
        topic: The topic to research
    
    Returns:
        A dictionary with the research summary
    """
    # First, check if we have relevant knowledge
    knowledge = await query_knowledge(
        query=f"Information about {topic}",
        max_results=5
    )
    
    # Build context from knowledge base
    context = "\n".join([r["content"] for r in knowledge.get("results", [])])
    
    # Trigger the researcher agent with context
    result = await trigger_agent(
        agent_name="researcher",
        payload={"topic": topic, "context": context}
    )
    
    return {
        "topic": topic,
        "summary": result["response"],
        "sources": len(knowledge.get("results", []))
    }

The custom tool above can be used in your agent YAML just like any other tool:

tools:
  - orchestration.research_and_summarize

Parameters

Return Value

Returns: run_id, status ("completed", "failed", or "timeout"),response (the agent's output), error (if failed). If wait_for_response=False, only run_id is returned.

Parameters

Exactly one of delay or unix_timestamp must be provided. Maximum scheduling window is 7 days into the future.

Return Value

Returns: run_id, scheduled_at (ISO 8601 UTC timestamp), status ("scheduled"). The tool always returns immediately without waiting for the agent to execute.

Examples

Using a relative delay:

# Schedule a report in 2 hours and 30 minutes
result = await trigger_agent_at(
    agent_name="report-generator",
    payload={"report_type": "daily"},
    delay={"h": 2, "m": 30}
)
# Returns: {"run_id": "...", "scheduled_at": "2026-03-18T16:30:00+00:00", "status": "scheduled"}

Using an absolute timestamp:

# Schedule at a specific time (Unix timestamp)
import time
target_time = time.time() + 86400  # 24 hours from now

result = await trigger_agent_at(
    agent_name="cleanup-agent",
    payload={"scope": "all"},
    unix_timestamp=target_time
)

Parameters

Return Value

Returns a dictionary with:

• results - List of search results, each containing:
  • title - Page title
  • url - Page URL
  • content - Snippet of page content

Parameters

Return Value

Returns a dictionary with:

• markdown - The page content converted to markdown
• url - The URL that was fetched

Available tools

Full parameter reference, return values, and filter operators: Database tools docs.