Benchmark sparse vs dense ternary matrix multiplication. Reports sparsity ratio, multiply-op count for both methods, and speedup factor. Demonstrates the @sparseskip efficiency gain.
Part of the Ternary Intelligence Stack server.
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AI agents call sparse_benchmark to retrieve information from Ternary Intelligence Stack 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 sparse_benchmark 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": {
"sparse_benchmark": {}
}
}See the full Ternary Intelligence Stack policy for all 34 tools.
These attack patterns abuse exactly the kind of access sparse_benchmark 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.
Benchmark sparse vs dense ternary matrix multiplication. Reports sparsity ratio, multiply-op count for both methods, and speedup factor. Demonstrates the @sparseskip efficiency gain.. It is categorised as a Read tool in the Ternary Intelligence Stack MCP Server, which means it retrieves data without modifying state.
Register the Ternary Intelligence Stack MCP server in PolicyLayer and add a rule for sparse_benchmark: 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 Ternary Intelligence Stack. Nothing to install.
sparse_benchmark 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 sparse_benchmark 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 sparse_benchmark. 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.
sparse_benchmark is provided by the Ternary Intelligence Stack MCP server (rfi-irfos/ternlang). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 34 Ternary Intelligence Stack tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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