Run a free, zero-LLM-cost pre-submission scoring of an academic paper.
AI agents call pre_check_paper to retrieve information from Science Ai without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and analyzes paper content to generate a quality score prior to submission. It has no side effects—it does not create, modify, delete, execute code, move money, or trigger external operations. The user can act on the scoring result, but the tool itself only reads and evaluates the paper. This is a classic Read operation.
From the tool's definition The tool description states it runs a 'free, zero-LLM-cost pre-submission scoring' of an academic paper. 'Scoring' indicates analysis and evaluation of existing data with no modification or execution of external operations.
Attacks that exploit this kind of access
Run a free, zero-LLM-cost pre-submission scoring of an academic paper. It is categorised as a Read tool in the Science Ai MCP Server, which means it retrieves data without modifying state.
Register the Science Ai MCP server in PolicyLayer and add a rule for pre_check_paper: 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 Science Ai. Nothing to install.
pre_check_paper 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 pre_check_paper 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 pre_check_paper. 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.
pre_check_paper is provided by the Science Ai MCP server (selfpy/science-ai-mcp-server). 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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