splitifi_predict_core
Predict Core Prediction case outcome using ML models trained on 3.52B+ court records. Provide jurisdiction and case_facts (case_type, jurisdiction, complexity, procedural_stage, risk_factors).
This record as markdown: /tools/io-github-mysplitifi-splitifi-mcp/splitifi-predict-core.md
What splitifi_predict_core does on Splitifi Intelligence MCP
AI agents call splitifi_predict_core to retrieve information from Splitifi Intelligence MCP without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
judge_id | string | — | Optional — judge ID for judge-specific modifier |
case_facts | object | Yes | Case details for Core Prediction. Key fields: case_type, jurisdiction, complexity, procedural_stage, risk_factors |
jurisdiction | string | Yes | State/province/country code, e.g. "TX", "CA", "ON" |
Parameters from the server's own tool schema.
Why splitifi_predict_core is rated Low
This tool queries a machine learning model to generate predictive insights about legal case outcomes. While the predictions could influence high-stakes decisions (litigation strategy, settlement negotiations), the tool itself performs only a retrieval operation with no side effects on systems, data, or finances.
From the tool's definition Tool description states 'Predict' outcome using ML models trained on court records. The inputs are jurisdictional and case metadata (case_type, jurisdiction, complexity, procedural_stage, risk_factors) — all read-only queries.
Attacks that exploit this kind of access
The rule that runs splitifi_predict_core safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Splitifi Intelligence MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For splitifi_predict_core, this is the rule to start with:
splitifi_predict_core is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Splitifi Intelligence MCP, apply this rule, and every splitifi_predict_core call is checked against it from then on.
Questions about splitifi_predict_core
Predict Core Prediction case outcome using ML models trained on 3.52B+ court records. Provide jurisdiction and case_facts (case_type, jurisdiction, complexity, procedural_stage, risk_factors). It is categorised as a Read tool in the Splitifi Intelligence MCP MCP Server, which means it retrieves data without modifying state.
splitifi_predict_core accepts 3 parameters: judge_id, case_facts, jurisdiction. Required: case_facts, jurisdiction. The full parameter table on this page comes from the server's own tool schema.
Register the Splitifi Intelligence MCP server in PolicyLayer and add a rule for splitifi_predict_core: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Splitifi Intelligence MCP. Nothing to install.
splitifi_predict_core is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the splitifi_predict_core rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for splitifi_predict_core. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
splitifi_predict_core is provided by the Splitifi Intelligence MCP server (splitifi-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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