Bayesian patent investment simulation with data-driven priors. Three modes: "init" builds priors from patent data, "update" incorporates user's private information via Bayesian updating, "simulate" runs Monte Carlo simulation. All prior parameters are evidenced by patent/GDELT data. Args: mode: "...
Part of the Patent Space server.
Free to start. No card required.
AI agents invoke tool_bayesian_scenario to trigger processes or run actions in Patent Space. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
tool_bayesian_scenario can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"tool_bayesian_scenario": {
"limits": [
{
"counter": "tool_bayesian_scenario_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Patent Space policy for all 29 tools.
These attack patterns abuse exactly the kind of access tool_bayesian_scenario gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Bayesian patent investment simulation with data-driven priors. Three modes: "init" builds priors from patent data, "update" incorporates user's private information via Bayesian updating, "simulate" runs Monte Carlo simulation. All prior parameters are evidenced by patent/GDELT data. Args: mode: "init" (start scenario), "update" (adjust parameter), "simulate" (run). technology: Cluster ID or tech description (required for init). firm_query: Optional firm name for context. investment_cost: Investment amount in 万円 (default: 10000). time_horizon_years: Analysis period (default: 10). session_id: Session ID from init (required for update/simulate). parameter: Parameter name to update (for update mode). user_value: User's estimated value (for update mode). user_confidence: 0-1 confidence in user value (default: 0.5). Returns: Init: priors with evidence. Update: posterior distribution. Simulate: NPV distribution, cashflow, breakeven, sensitivity.. It is categorised as a Execute tool in the Patent Space MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Patent Space MCP server in PolicyLayer and add a rule for tool_bayesian_scenario: 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 Patent Space. Nothing to install.
tool_bayesian_scenario is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the tool_bayesian_scenario 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 tool_bayesian_scenario. 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.
tool_bayesian_scenario is provided by the Patent Space MCP server (Rei02061986/patent-space-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 29 Patent Space tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.