Low Risk

trit_vector

Multi-dimensional ternary evidence aggregation — the full agent reasoning tool. Provide named evidence dimensions each with a scalar value [-1.0, +1.0] and importance weight. Computes weighted-mean aggregate TritScalar and returns: aggregate (trit+confidence+is_actionable), per-dimension breakdow...

Part of the Ternary Intelligence Stack server.

trit_vector is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call trit_vector 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 trit_vector 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "trit_vector": {}
  }
}

See the full Ternary Intelligence Stack policy for all 34 tools.

Get this rule live on your own Ternary Intelligence Stack server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access trit_vector gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so trit_vector only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the trit_vector tool do? +

Multi-dimensional ternary evidence aggregation — the full agent reasoning tool. Provide named evidence dimensions each with a scalar value [-1.0, +1.0] and importance weight. Computes weighted-mean aggregate TritScalar and returns: aggregate (trit+confidence+is_actionable), per-dimension breakdown, dominant dimension, and plain-language recommendation.. It is categorised as a Read tool in the Ternary Intelligence Stack MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on trit_vector? +

Register the Ternary Intelligence Stack MCP server in PolicyLayer and add a rule for trit_vector: 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.

What risk level is trit_vector? +

trit_vector is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit trit_vector? +

Yes. Add a rate_limit block to the trit_vector 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.

How do I block trit_vector completely? +

Set action: deny in the PolicyLayer policy for trit_vector. 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.

What MCP server provides trit_vector? +

trit_vector 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.

Enforce policy on every Ternary Intelligence Stack tool call.

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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