Record a review decision: 'kept' | 'merged' | 'ignored'.
AI agents use files_dedup_review to create or update resources in M3 Memory — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your M3 Memory environment.
This tool writes/records a decision outcome for a deduplication review. It modifies stored state by recording one of three decision types. 'Merged' could have destructive implications (combining records), but the primary action is recording/writing a decision rather than irreversible deletion, so Write is the most appropriate category.
From the tool's definition 'Record a review decision: kept | merged | ignored'
Documented attack patterns abuse exactly the kind of access files_dedup_review gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and M3 Memory, and nothing reaches the server without passing your rules. This is the rule we recommend for files_dedup_review:
{
"version": "1",
"default": "deny",
"tools": {
"files_dedup_review": {
"limits": [
{
"counter": "files_dedup_review_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}files_dedup_review 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.
Free to start. No card required.
Record a review decision: 'kept' | 'merged' | 'ignored'. It is categorised as a Write tool in the M3 Memory MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the M3 Memory MCP server in PolicyLayer and add a rule for files_dedup_review: 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 M3 Memory. Nothing to install.
files_dedup_review is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the files_dedup_review 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 files_dedup_review. 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.
files_dedup_review is provided by the M3 Memory MCP server (skynetcmd/m3-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from M3 Memory, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
43 M3 Memory tools catalogued and risk-classified — across an index of 43,000+ MCP servers.