add_decision · Faulkner DB MCP: Risk & Policy

WHAT IT DOES

What add_decision does on Faulkner DB

AI agents use add_decision to create or update resources in Faulkner DB — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Faulkner DB environment.

WHY IT NEEDS A POLICY

Why add_decision needs a policy

This tool creates new entries in a temporal knowledge graph by recording architectural decisions. It is reversible (decisions can be updated or removed by other tools), has no irreversible effects, and carries moderate risk if misused—an agent could record false or misleading architectural decisions that corrupt organizational knowledge, but this is recoverable and does not execute code or delete data.

From the tool's definition Tool description states 'Record an architectural decision' — the verb 'record' indicates creation/insertion of new data into the knowledge graph system. No deletion, destructive operations, code execution, or financial transactions are implied.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

add_decision Rate-limited

add_decision stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "add_decision": {
      "limits": [
        {
          "counter": "add_decision_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Faulkner DB, so you can run agents against it safely.

FAQ

Questions about add_decision

What does the add_decision tool do? +

Record an architectural decision with rationale, alternatives, and related decisions. It is categorised as a Write tool in the Faulkner DB MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on add_decision? +

Register the Faulkner DB MCP server in PolicyLayer and add a rule for add_decision: 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 Faulkner DB. Nothing to install.

What risk level is add_decision? +

add_decision is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit add_decision? +

Yes. Add a rate_limit block to the add_decision 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 add_decision completely? +

Set action: deny in the PolicyLayer policy for add_decision. 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 add_decision? +

add_decision is provided by the Faulkner DB MCP server (platano78/faulkner-db). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.