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cct15

Futuristic Risk Intelligence

get_conflict_risks

Analyze geopolitical conflict risk probabilities for major regions to assess exposure for trading and risk management decisions.

Instructions

Get current geopolitical conflict risk probabilities for 6 major regions: Russia-Ukraine, Iran-Israel/US, Israel-Palestine, China-Taiwan, India-Pakistan, US-Latin America. Each conflict includes probability of escalation, ceasefire, regime change, and other events within 1-day, 7-day, and 30-day horizons. Probabilities are derived from proprietary multi-source modeling. Updated daily. Use this to assess geopolitical risk exposure for trading or risk management.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conflict_idNoOptional: filter to a single conflict region. Valid values: russia_ukraine, iran_israel_us, israel_palestine, china_taiwan, india_pakistan, us_latam. Omit to get all 6 regions.

Implementation Reference

  • The handle_get_conflict_risks function retrieves and filters conflict data from conflicts.json.
    def handle_get_conflict_risks(args: dict) -> str:
        data = _load_json("conflicts.json")
        if "error" in data:
            return json.dumps(data)
    
        conflict_id = args.get("conflict_id")
        if conflict_id:
            filtered = [c for c in data.get("conflicts", []) if c["conflict_id"] == conflict_id]
            if not filtered:
                return json.dumps({"error": f"Conflict '{conflict_id}' not found"})
            data["conflicts"] = filtered
    
        return json.dumps(data, indent=2)
  • The MCP tool registration and schema definition for 'get_conflict_risks'.
    {
        "name": "get_conflict_risks",
        "description": (
            "Get current geopolitical conflict risk probabilities for 6 major regions: "
            "Russia-Ukraine, Iran-Israel/US, Israel-Palestine, China-Taiwan, India-Pakistan, US-Latin America. "
            "Each conflict includes probability of escalation, ceasefire, regime change, and other events "
            "within 1-day, 7-day, and 30-day horizons. "
            "Probabilities are derived from proprietary multi-source modeling. "
            "Updated daily. Use this to assess geopolitical risk exposure for trading or risk management."
        ),
        "inputSchema": {
            "type": "object",
            "properties": {
                "conflict_id": {
                    "type": "string",
                    "description": (
                        "Optional: filter to a single conflict region. "
                        "Valid values: russia_ukraine, iran_israel_us, israel_palestine, "
                        "china_taiwan, india_pakistan, us_latam. "
                        "Omit to get all 6 regions."
                    ),
                    "enum": [
                        "russia_ukraine", "iran_israel_us", "israel_palestine",
                        "china_taiwan", "india_pakistan", "us_latam",
                    ],
                },
            },
            "required": [],
        },
    },
  • Registration of the handle_get_conflict_risks handler within the TOOL_HANDLERS dictionary.
    TOOL_HANDLERS = {
        "get_conflict_risks": handle_get_conflict_risks,
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Discloses critical behavioral traits: data provenance ('proprietary multi-source modeling'), update frequency ('Updated daily'), and output structure (probabilities for escalation/ceasefire/regime change across 1/7/30-day horizons). Lacks operational details like rate limits or caching, but covers data freshness and scope thoroughly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three well-structured sentences: (1) scope and regions, (2) data content and methodology, (3) usage guidance. No wasted words; every clause provides necessary information. Front-loaded with the core action 'Get current geopolitical conflict risk probabilities' immediately establishing purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description comprehensively details the return data: specific event types (escalation, ceasefire, regime change), time horizons (1/7/30-day), and scope (6 regions). With only one optional parameter fully documented in schema, the description provides sufficient completeness for an agent to predict both input requirements and output structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% description coverage with complete enum documentation. Description lists the 6 regions (Russia-Ukraine, etc.) which maps to enum values, but this largely repeats the schema's content. With schema coverage already comprehensive, baseline 3 is appropriate as description adds minimal semantic value beyond parameter mapping.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses specific verb 'Get' with clear resource 'geopolitical conflict risk probabilities' and enumerates all 6 supported regions. It clearly distinguishes from sibling tools: 'get_maritime_traffic' (shipping) and 'get_political_events' (general politics) by specifying probabilistic conflict forecasting for specific military/political flashpoints.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states the use case: 'Use this to assess geopolitical risk exposure for trading or risk management.' This provides clear context for when to invoke the tool. Does not explicitly name sibling alternatives, but the domain specificity (conflict probabilities vs. maritime traffic) makes differentiation clear without negative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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