get_skill
AI agents call get_skill to retrieve information from RunWhen Platform MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The name 'get_skill' follows standard retrieval naming conventions (get = read operation). In the context of the RunWhen Platform MCP, which manages skills/SLXs and configurations, retrieving skill information represents a read-only query with no destructive, financial, or code execution implications.
From the tool's definition Tool name 'get_skill' suggests retrieval of skill data with no apparent side effects. Description is empty, limiting definitive assessment.
Attacks that exploit this kind of access
get_skill. It is categorised as a Read tool in the RunWhen Platform MCP MCP Server, which means it retrieves data without modifying state.
Register the RunWhen Platform MCP server in PolicyLayer and add a rule for get_skill: 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 RunWhen Platform MCP. Nothing to install.
get_skill is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_skill 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 get_skill. 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.
get_skill is provided by the RunWhen Platform MCP server (runwhen-contrib/runwhen-platform-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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