Run the Design Intake Assessment - the FIRST step of the Design Intelligence pipeline after PRD. Captures comprehensive user design preferences: brand identity, colors, typography, layout, mood, animation, component styles, platform targets, accessibility requirements, competitor intelligence, an...
AI agents use design_intake to create or update resources in RC Engine — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your RC Engine environment.
The tool captures user input and writes structured output to a file (DESIGN-INTAKE.md). While it performs analysis and scoring, its primary side effect is persisting data to disk. This is a reversible write operation — the file can be overwritten or deleted — so Write is the appropriate category rather than Execute.
From the tool's definition Saves to rc-method/design/DESIGN-INTAKE.md
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
Run the Design Intake Assessment - the FIRST step of the Design Intelligence pipeline after PRD. Captures comprehensive user design preferences: brand identity, colors, typography, layout, mood, animation, component styles, platform targets, accessibility requirements, competitor intelligence, and screen inventory. Evaluates all inputs against ICP expectations. Returns alignment score (0-100), verdict (proceed/proceed_with_adjustments/reconsider), and extracted design constraints that feed into every downstream design tool. Saves to rc-method/design/DESIGN-INTAKE.md. It is categorised as a Write tool in the RC Engine MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the RC Engine MCP server in PolicyLayer and add a rule for design_intake: 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_intake is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the design_intake 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_intake. 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_intake 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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