Free tier. Renders the MMHW standard only — CESMM4, NRM2 and SMM7 require a paid tier. Anonymous callers welcome. Composite drainage inlet: precast gully pot with trap, ductile-iron grating, optional kerb outlet, and a short connection drain to the carrier sewer. The connection drain re-uses the ...
Risk signalsHigh parameter count (25 properties)
Part of the Civilquants server.
Free to start. No card required.
AI agents invoke compute_gully to trigger processes or run actions in Civilquants. 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.
compute_gully 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": {
"compute_gully": {
"limits": [
{
"counter": "compute_gully_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Civilquants policy for all 52 tools.
These attack patterns abuse exactly the kind of access compute_gully 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.
Free tier. Renders the MMHW standard only — CESMM4, NRM2 and SMM7 require a paid tier. Anonymous callers welcome. Composite drainage inlet: precast gully pot with trap, ductile-iron grating, optional kerb outlet, and a short connection drain to the carrier sewer. The connection drain re-uses the bedding primitive. Four-standard rendering with component-aware sub-codes (CESMM4 K.6.x, NRM2 33.8.x, MMHW 500.7.x, SMM7 R12.3.6.x). Example params: pot_internal_diameter_mm=450 mm (300–750), pot_depth_m=0.9 m (0.45–2.5), pot_wall_thickness_mm=60 mm (50–100). Example call: {"params": {"pot_internal_diameter_mm": 450, "pot_depth_m": 0.9, "pot_wall_thickness_mm": 60}, "standard": "MMHW"}. Omitted parameters use sensible engineering defaults. Pass deliverables=["xlsx"] to also receive a one-shot Excel BoQ download URL in the same call.. It is categorised as a Execute tool in the Civilquants MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Civilquants MCP server in PolicyLayer and add a rule for compute_gully: 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 Civilquants. Nothing to install.
compute_gully 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 compute_gully 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 compute_gully. 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.
compute_gully is provided by the Civilquants MCP server (https://api.civilquants.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 52 Civilquants 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.