Pre-submission duplicate-publication and salami-slicing check.
AI agents call check_duplicate_publication 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 existing publication data to identify duplicates and problematic submission patterns. It has no side effects: it does not create, modify, delete, or execute code. The operation is purely informational/diagnostic, making it a Read category tool. Severity is low because misuse would only affect the accuracy of duplicate detection advice, with no destructive consequences.
From the tool's definition The tool performs a 'check' and 'pre-submission' validation operation. It queries/detects duplicate publications and salami-slicing patterns without modifying, deleting, or executing external operations.
Attacks that exploit this kind of access
Pre-submission duplicate-publication and salami-slicing check. 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 check_duplicate_publication: 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.
check_duplicate_publication 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 check_duplicate_publication 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 check_duplicate_publication. 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.
check_duplicate_publication 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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