Run the full Design Intelligence pipeline in sequence: brand_import → design_intake → design_research_brief → copy_research + copy_generate → ux_design → auto-select → design_challenge. Requires PRD to exist (run rc_define first). Captures user design preferences via design_intake, generates real...
AI agents invoke design_pipeline to trigger actions in RC Engine. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool executes a comprehensive pipeline with multiple interdependent steps that produce artifacts (design options, wireframes, copy, reports). While primarily a product design tool, it performs triggered operations whose outcomes depend on arguments and user input, and creates substantive outputs that persist. It is not merely reading data (Read), as it generates and produces new design artifacts.
From the tool's definition The tool 'Run the full Design Intelligence pipeline in sequence' executes a multi-step orchestrated process that chains together brand imports, design intake, research briefs, copy generation, UX design, auto-selection, and design challenges.
Attacks that exploit this kind of access
Run the full Design Intelligence pipeline in sequence: brand_import → design_intake → design_research_brief → copy_research + copy_generate → ux_design → auto-select → design_challenge. Requires PRD to exist (run rc_define first). Captures user design preferences via design_intake, generates real copy, then produces research-backed design options with wireframes using that copy. Returns a combined report with all artifacts. Each step can also be called individually for more control. It is categorised as a Execute tool in the RC Engine MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the RC Engine MCP server in PolicyLayer and add a rule for design_pipeline: 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 RC Engine. Nothing to install.
design_pipeline is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the design_pipeline 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 design_pipeline. 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.
design_pipeline is provided by the RC Engine MCP server (originalrashmi/rc-engine-product-framework). 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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