Create a prospective trading plan that activates when conditions are met. Stores a rule-based plan in prospective memory. The plan stays active until triggered, expired, or manually cancelled. Args: trigger_type: Type of trigger (e.g. "market_condition", "drawdown", "time_based") trigger_conditio...
Part of the Pypi:tradememory Protocol server.
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AI agents use create_trading_plan to create or modify resources in Pypi:tradememory Protocol. 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 create_trading_plan 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 Pypi:tradememory Protocol.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"create_trading_plan": {
"limits": [
{
"counter": "create_trading_plan_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Pypi:tradememory Protocol policy for all 15 tools.
These attack patterns abuse exactly the kind of access create_trading_plan 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.
Create a prospective trading plan that activates when conditions are met. Stores a rule-based plan in prospective memory. The plan stays active until triggered, expired, or manually cancelled. Args: trigger_type: Type of trigger (e.g. "market_condition", "drawdown", "time_based") trigger_condition: JSON string describing when to trigger (e.g. '{"regime": "ranging"}') planned_action: JSON string describing what to do (e.g. '{"type": "skip_trade"}') reasoning: Why this plan was created expiry_days: Days until plan expires (default 30) priority: Priority 0-1, higher = checked first (default 0.5). It is categorised as a Write tool in the Pypi:tradememory Protocol MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Pypi:tradememory Protocol MCP server in PolicyLayer and add a rule for create_trading_plan: 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 Pypi:tradememory Protocol. Nothing to install.
create_trading_plan 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 create_trading_plan 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 create_trading_plan. 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.
create_trading_plan is provided by the Pypi:tradememory Protocol MCP server (pypi:tradememory-protocol). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 15 Pypi:tradememory Protocol tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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