TalentPerformer

Real Estate

Real Estate

Trend Tracker

You are a Trend Tracker Agent. You run the full process: call Exa trend research with location (and timeframe), normalize the output, then save to Documents/.

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Purpose

You are a Trend Tracker Agent. You run the full process: call Exa trend research with location (and timeframe), normalize the output, then save to Documents/.

AI-Powered IntelligenceAdvanced AI capabilities for automated processing and analysis

Enterprise ReadyBuilt for production with security, scalability, and reliability

Seamless IntegrationEasy to integrate with your existing systems and workflows

Agent Capabilities

This agent is equipped with the following advanced capabilities:

Available Tools

Reasoning Tools

ReasoningTools from agno framework

Exa Trend Tracker Research

Research real estate market outlook for a location over a timeframe. Returns raw JSON string from Exa.

def exa_trend_tracker_research(location: str, timeframe: str = "20252026") -> str:
    """Research real estate market outlook for a location over a timeframe. Returns raw JSON string from Exa."""
    completion = client.chat.completions.create(
        model="exa-research",
        messages=[
            {
                "role": "user",
                "content": dedent(f"""
                Research the real estate market outlook for {location} over {timeframe}.

                Return your findings as a single JSON object with these fields:
                - location: string(the city/region being analyzed)
                - as_of: string(latest date reference mentioned, e.g. "Q3 2025" or "September 2025")
                - trend_horizon: string(the forecast period, e.g. "20252026", "next 12 months")
                - price_forecast_percent_range: string(expected % change in residential property prices, e.g. "-1% to +2%")
                - rent_forecast_percent_range: string(expected % change in residential rents, e.g. "+3% to +6%")
                - demand_drivers: array of strings(factors supporting growth)
                - risks: array of strings(factors that could push downside)
                - outlook: string(short narrative, 23 sentences)
                - scenarios: object with base_case, optimistic_case, pessimistic_case(strings)
                - sources: array of strings(35 credible URLs)
                - report: string(full written report)

                Important:
                1. Always include explicit percentages.
                2. Keep all values inside the JSON object.
                3. If data is missing, include the field with value "N/A".
                4. Only include real estate fundamentals; do not mention financing, mortgages, or interest rates.
                """),
            }
        ],
        stream=False,
    )
    full_content = ""
    for chunk in completion:
        if chunk.choices and chunk.choices[0].delta.content:
            full_content += chunk.choices[0].delta.content
    return full_content

Get Trend Tracker Last Data

Read last trend tracker report from Documents/trend_tracker_last_data.json. Returns empty string if missing.

def get_trend_tracker_last_data() -> str:
    """Read last trend tracker report from Documents/trend_tracker_last_data.json. Returns empty string if missing."""
    path = DOCUMENTS_DIR / "trend_tracker_last_data.json"
    if not path.exists():
        return ""
    return path.read_text(encoding="utf-8")

Save Trend Tracker Last Data

Save trend tracker result to Documents/trend_tracker_last_data.json. Accepts JSON string or dict.

def save_trend_tracker_last_data(data: str | dict) -> str:
    """Save trend tracker result to Documents/trend_tracker_last_data.json. Accepts JSON string or dict."""
    obj = _parse_json_input(data)
    path = DOCUMENTS_DIR / "trend_tracker_last_data.json"
    path.write_text(json.dumps(obj, ensure_ascii=False, indent=2), encoding="utf-8")
    return f"Saved to {path}"

Required Inputs

Generated Outputs

Business Value

Automated processing reduces manual effort and improves accuracy

Consistent validation logic ensures compliance and audit readiness

Early detection of issues minimizes downstream risks and costs

Graph

Trend Tracker preview

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