Gain/Loss experiment — disable each interrupt one at a time, measure production recovered. Reveals the ACTUAL impact of each failure mode (Gain ≠ Loss: removing one lets others fire more often). Available on bs1-leds, bs3-leds, bs4-ct, bs4-leds. Use when the user asks 'what if we fixed X?' / 'whi...
Part of the ReliaSim server.
Free to start. No card required.
AI agents invoke run_gain_loss to trigger processes or run actions in ReliaSim. 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.
run_gain_loss 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": {
"run_gain_loss": {
"limits": [
{
"counter": "run_gain_loss_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full ReliaSim policy for all 7 tools.
These attack patterns abuse exactly the kind of access run_gain_loss 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.
Gain/Loss experiment — disable each interrupt one at a time, measure production recovered. Reveals the ACTUAL impact of each failure mode (Gain ≠ Loss: removing one lets others fire more often). Available on bs1-leds, bs3-leds, bs4-ct, bs4-leds. Use when the user asks 'what if we fixed X?' / 'which interrupt matters most if we actually fixed it?' / 'show me the Pareto'. ANTI-FABRICATION: per-interrupt recovered-production numbers come from real dys-cli runs. Quote VERBATIM; the Gain ≠ Loss interaction is exactly the kind of figure LLMs are prone to fabricate — don't.. It is categorised as a Execute tool in the ReliaSim MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ReliaSim MCP server in PolicyLayer and add a rule for run_gain_loss: 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 ReliaSim. Nothing to install.
run_gain_loss 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 run_gain_loss 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 run_gain_loss. 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.
run_gain_loss is provided by the ReliaSim MCP server (https://reliasim.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 7 ReliaSim 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.