Log a lesson-progress event for the session
AI agents use maker_log_progress to create or update resources in Crow — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Crow environment.
This tool writes/creates a progress log entry for a session. It is a write operation (creating a new log record) with no indication of destructive, financial, or execution side effects. The blast radius is low as it only records progress data.
From the tool's definition Log a lesson-progress event for the session
Documented attack patterns abuse exactly the kind of access maker_log_progress gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Crow, and nothing reaches the server without passing your rules. This is the rule we recommend for maker_log_progress:
{
"version": "1",
"default": "deny",
"tools": {
"maker_log_progress": {
"limits": [
{
"counter": "maker_log_progress_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} maker_log_progress 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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Log a lesson-progress event for the session. It is categorised as a Write tool in the Crow MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Crow MCP server in PolicyLayer and add a rule for maker_log_progress: 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 Crow. Nothing to install.
maker_log_progress 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 maker_log_progress 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 maker_log_progress. 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.
maker_log_progress is provided by the Crow MCP server (kh0pper/crow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Crow, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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576 Crow tools catalogued and risk-classified — across an index of 43,000+ MCP servers.