Free tier. Renders the MMHW standard only — CESMM4, NRM2 and SMM7 require a paid tier. Anonymous callers welcome. In-situ reinforced concrete cantilever retaining wall with toe, heel, and stem. Includes excavation, blinding, drainage, and backfill quantities. Example params: stem_height=4 m (2–8)...
Risk signalsHigh parameter count (23 properties)
Part of the Civilquants server.
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AI agents use compute_cantilever_wall to create or modify resources in Civilquants. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call compute_cantilever_wall repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Civilquants.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"compute_cantilever_wall": {
"limits": [
{
"counter": "compute_cantilever_wall_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Civilquants policy for all 52 tools.
These attack patterns abuse exactly the kind of access compute_cantilever_wall gives an agent. Each links to the full case and the policy that stops it:
Other write 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. In-situ reinforced concrete cantilever retaining wall with toe, heel, and stem. Includes excavation, blinding, drainage, and backfill quantities. Example params: stem_height=4 m (2–8), stem_thickness_top=0.3 m (0.2–0.6), stem_thickness_bottom=0.45 m (0.25–0.9). Example call: {"params": {"stem_height": 4, "stem_thickness_top": 0.3, "stem_thickness_bottom": 0.45}, "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. Pass freeboard (clearance below the wall top, m) instead of the retained-height field to set the retained fill by clearance — the engine back-calculates it as stem − freeboard. Supplying both is rejected.. It is categorised as a Write tool in the Civilquants MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Civilquants MCP server in PolicyLayer and add a rule for compute_cantilever_wall: 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_cantilever_wall is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the compute_cantilever_wall 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_cantilever_wall. 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_cantilever_wall 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.
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