Simulates 3 failure scenarios (Best/Likely/Worst) for an idea with quantified expected loss in hours and money. Fetches multi-source market data (Reddit, HN, GitHub, Polymarket) to ground predictions in real signals. Use this when the user wants to understand the RISK of an idea without the full ...
AI agents call loss_simulation to retrieve information from openGlad without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool performs data retrieval and analysis (querying Reddit, HN, GitHub, Polymarket) and computational simulation to generate risk forecasts. It does not create, modify, delete, or transact on any data. The 'expected loss' figures are projections, not actual financial operations. This is fundamentally a Read operation: it retrieves external data and computes insights without side effects.
From the tool's definition Simulates failure scenarios and fetches market data for analysis; no modifications to data, no code execution, no deletions, no financial transactions.
Documented attack patterns abuse exactly the kind of access loss_simulation gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and openGlad, and nothing reaches the server without passing your rules. This is the rule we recommend for loss_simulation:
{
"version": "1",
"default": "deny",
"tools": {
"loss_simulation": {}
}
}loss_simulation is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Simulates 3 failure scenarios (Best/Likely/Worst) for an idea with quantified expected loss in hours and money. Fetches multi-source market data (Reddit, HN, GitHub, Polymarket) to ground predictions in real signals. Use this when the user wants to understand the RISK of an idea without the full run_the_bet pipeline. It is categorised as a Read tool in the openGlad MCP Server, which means it retrieves data without modifying state.
Register the openGlad MCP server in PolicyLayer and add a rule for loss_simulation: 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 openGlad. Nothing to install.
loss_simulation 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 loss_simulation 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 loss_simulation. 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.
loss_simulation is provided by the openGlad MCP server (tuguberk/openglad). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from openGlad, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
13 openGlad tools catalogued and risk-classified — across an index of 43,000+ MCP servers.