List all available playbooks with their IDs, names, platforms, and success rates.
AI agents call playbook_list to retrieve information from ScreenHand without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns metadata about available playbooks (IDs, names, platforms, success rates) without triggering any side effects, executing code, or modifying state. It is a straightforward inventory/discovery operation.
From the tool's definition Tool description states 'List all available playbooks' — a retrieval operation with no modification, deletion, or execution of actions. The verb 'list' and the absence of any action words (create, delete, run, execute) clearly indicate a read-only query.
Documented attack patterns abuse exactly the kind of access playbook_list gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and ScreenHand, and nothing reaches the server without passing your rules. This is the rule we recommend for playbook_list:
{
"version": "1",
"default": "deny",
"tools": {
"playbook_list": {}
}
}playbook_list is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List all available playbooks with their IDs, names, platforms, and success rates. It is categorised as a Read tool in the ScreenHand MCP Server, which means it retrieves data without modifying state.
Register the ScreenHand MCP server in PolicyLayer and add a rule for playbook_list: 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 ScreenHand. Nothing to install.
playbook_list 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 playbook_list 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 playbook_list. 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.
playbook_list is provided by the ScreenHand MCP server (manushi4/screenhand). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from ScreenHand, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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89 ScreenHand tools catalogued and risk-classified — across an index of 43,000+ MCP servers.