Approve a decision currently in the memoir-style review queue (review_status=
AI agents use approve_decision to create or update resources in Trace — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Trace environment.
The tool approves (transitions state of) decisions in a review queue. This is a state modification action that persists changes to decision records, fitting the Write category (reversible modification).
From the tool's definition 'Approve a decision currently in the memoir-style review queue' — this modifies the review_status of a decision, changing it from pending to approved state. It creates or updates metadata about code decisions.
Documented attack patterns abuse exactly the kind of access approve_decision gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Trace, and nothing reaches the server without passing your rules. This is the rule we recommend for approve_decision:
{
"version": "1",
"default": "deny",
"tools": {
"approve_decision": {
"limits": [
{
"counter": "approve_decision_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}approve_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.
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Approve a decision currently in the memoir-style review queue (review_status=. It is categorised as a Write tool in the Trace MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Trace MCP server in PolicyLayer and add a rule for approve_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 Trace. Nothing to install.
approve_decision 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 approve_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.
Set action: deny in the PolicyLayer policy for approve_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.
approve_decision is provided by the Trace MCP server (nikolai-vysotskyi/trace-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 178 Trace tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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178 Trace tools catalogued and risk-classified — across an index of 42,500+ MCP servers.