Publish a course: sets is_published=true after validating that every lesson has content_url. Returns error if any lesson is still empty — run hivelearn_get_course_structure to diagnose.
Risk signalsBulk/mass operation — affects multiple targets
Part of the HiveLearn server.
Free to start. No card required.
AI agents use hivelearn_publish_course to create or modify resources in HiveLearn. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call hivelearn_publish_course repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach HiveLearn.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"hivelearn_publish_course": {
"limits": [
{
"counter": "hivelearn_publish_course_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full HiveLearn policy for all 43 tools.
These attack patterns abuse exactly the kind of access hivelearn_publish_course gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Publish a course: sets is_published=true after validating that every lesson has content_url. Returns error if any lesson is still empty — run hivelearn_get_course_structure to diagnose.. It is categorised as a Write tool in the HiveLearn MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the HiveLearn MCP server in PolicyLayer and add a rule for hivelearn_publish_course: 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 HiveLearn. Nothing to install.
hivelearn_publish_course 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 hivelearn_publish_course 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 hivelearn_publish_course. 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.
hivelearn_publish_course is provided by the HiveLearn MCP server (hivelearn-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 43 HiveLearn tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.