splitifi_predict_employment
Predict Employment / Labor case outcome using ML models trained on 3.52B+ court records. Provide jurisdiction and case_facts (claim_type, employment_duration, termination_reason, documentation_quality, protected_class).
This record as markdown: /tools/io-github-mysplitifi-splitifi-mcp/splitifi-predict-employment.md
What splitifi_predict_employment does on Splitifi Intelligence MCP
AI agents call splitifi_predict_employment 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 Employment / Labor. Key fields: claim_type, employment_duration, termination_reason, documentation_quality, protected_class |
jurisdiction | string | Yes | State/province/country code, e.g. "TX", "CA", "ON" |
Parameters from the server's own tool schema.
Why splitifi_predict_employment is rated Low
This tool retrieves predictive analytics from pre-trained ML models based on court records. It reads input parameters and queries a model to return outcome predictions—a classic Read operation with no side effects. While the predictions may inform high-stakes legal decisions, the tool itself performs no irreversible modifications, financial transactions, or command execution.
From the tool's definition Tool description explicitly states 'Predict' and 'using ML models trained on' historical data. Accepts inputs (jurisdiction, case_facts) and returns predictions with no indication of modifying, executing transactions, or destructively altering data.
Attacks that exploit this kind of access
The rule that runs splitifi_predict_employment 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_employment, this is the rule to start with:
splitifi_predict_employment 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_employment call is checked against it from then on.
Questions about splitifi_predict_employment
Predict Employment / Labor case outcome using ML models trained on 3.52B+ court records. Provide jurisdiction and case_facts (claim_type, employment_duration, termination_reason, documentation_quality, protected_class). It is categorised as a Read tool in the Splitifi Intelligence MCP MCP Server, which means it retrieves data without modifying state.
splitifi_predict_employment 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_employment: 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_employment 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_employment 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_employment. 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_employment 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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