Pre-mutation governance check: verifies a planned action against all accepted team decisions before any workspace changes occur. Returns blocked=true if the action conflicts with an accepted decision. Agents SHOULD call this before major workspace mutations (creating decisions, changing architect...
AI agents call tool_check_planned_action to retrieve information from Engrams without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Despite the governance context, this tool performs only a query/validation operation against existing data (team decisions). It has no side effects—it does not create, modify, delete, or execute external operations. It is purely informational, returning a compliance status to inform downstream decisions. The actual mutations it guards against are separate operations (handled by the post-write safety net mentioned).
From the tool's definition The tool 'check_planned_action' verifies and returns a boolean result (blocked=true/false) against stored decisions.
Documented attack patterns abuse exactly the kind of access tool_check_planned_action gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Engrams, and nothing reaches the server without passing your rules. This is the rule we recommend for tool_check_planned_action:
{
"version": "1",
"default": "deny",
"tools": {
"tool_check_planned_action": {}
}
}tool_check_planned_action is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Pre-mutation governance check: verifies a planned action against all accepted team decisions before any workspace changes occur. Returns blocked=true if the action conflicts with an accepted decision. Agents SHOULD call this before major workspace mutations (creating decisions, changing architecture, modifying patterns). This is the pre-check layer of the governance defense-in-depth system — even if skipped, the post-write safety net in _apply_governance_checks will still flag conflicts after the write. It is categorised as a Read tool in the Engrams MCP Server, which means it retrieves data without modifying state.
Register the Engrams MCP server in PolicyLayer and add a rule for tool_check_planned_action: 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 Engrams. Nothing to install.
tool_check_planned_action 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 tool_check_planned_action 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 tool_check_planned_action. 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.
tool_check_planned_action is provided by the Engrams MCP server (stevebrownlee/engrams). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Engrams, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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42 Engrams tools catalogued and risk-classified — across an index of 43,000+ MCP servers.