AI agents use clear_execution_counts to create or update resources in Ast Editor — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ast Editor environment.
The name 'clear_execution_counts' suggests resetting or clearing execution count metadata (likely Jupyter notebook cell execution counts). This is likely a Write operation that modifies metadata reversibly. However, the empty description significantly reduces confidence. It could also be considered Destructive if counts cannot be recovered, but 'clear' of metadata is typically reversible.
From the tool's definition Tool name: clear_execution_counts; description is empty/uninformative
Documented attack patterns abuse exactly the kind of access clear_execution_counts gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ast Editor, and nothing reaches the server without passing your rules. This is the rule we recommend for clear_execution_counts:
{
"version": "1",
"default": "deny",
"tools": {
"clear_execution_counts": {
"limits": [
{
"counter": "clear_execution_counts_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}clear_execution_counts 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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clear_execution_counts. It is categorised as a Write tool in the Ast Editor MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ast Editor MCP server in PolicyLayer and add a rule for clear_execution_counts: 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 Ast Editor. Nothing to install.
clear_execution_counts 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 clear_execution_counts 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 clear_execution_counts. 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.
clear_execution_counts is provided by the Ast Editor MCP server (kambleakash0/agent-skills). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Ast Editor, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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59 Ast Editor tools catalogued and risk-classified — across an index of 43,000+ MCP servers.