Get the actual Python code behind a community leaderboard strategy. Use after browse_community: pass an entry's id here to read its real feature_engineering() + strategy_config() source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to one_shot as community_id. Read...
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AI agents call get_strategy_code to retrieve information from Quantifyme without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though get_strategy_code only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"get_strategy_code": {}
}
}See the full Quantifyme policy for all 11 tools.
These attack patterns abuse exactly the kind of access get_strategy_code gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Get the actual Python code behind a community leaderboard strategy. Use after browse_community: pass an entry's id here to read its real feature_engineering() + strategy_config() source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to one_shot as community_id. Read-only, no signup needed. Args: community_id: The id of a community entry (from browse_community). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and code (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.. It is categorised as a Read tool in the Quantifyme MCP Server, which means it retrieves data without modifying state.
Register the Quantifyme MCP server in PolicyLayer and add a rule for get_strategy_code: 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 Quantifyme. Nothing to install.
get_strategy_code 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 get_strategy_code 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 get_strategy_code. 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.
get_strategy_code is provided by the Quantifyme MCP server (https://mcp.quantifyme.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 11 Quantifyme tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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